The global burden of cancer continues to grow, posing a significant public health challenge. Although cancer immunotherapy has shown significant efficacy, the response rate is not high. Therefore, the objective of our research was to identify the latest research trends and hotspots on biomarkers from 1993 to 2023. Data were collected from the database Web of Science core collection. Bibliometric analysis and visualization were conducted with CiteSpace(6.3.1), VOSviewer (v1.6.20), R-bibliometrix(v4.3.3), and Microsoft Excel(2019). A total of 2686 literatures were retrieved. The sheer annual volume of publications has shown a rapid upward trend since 2015. The United States has generated the most publications and Harvard University ranked as a leading institution. The global biomarker research on immune checkpoint inhibitors (ICIs) revealed regional differences and in-depth explorations should be promoted in developing countries. Although China has become the second largest country in terms of publication, the average citation per paper and the total link strength were both lower than the other countries. The research on biomarkers mainly concentrated upon the following aspects: PD-1/PD-L1, CTLA-4, gene expression, adverse events, total mutational burden (TMB), body mass index (BMI), gut microbiota, cd8(+)/cd4(+) t-cells, and blood-related biomarkers such as lactate dehydrogenase (LDH), neutrophil-lymphocyte ratio (NLR), cytokines. Furthermore, "artificial intelligence" and "machine learning" have become the most important research hotspot over the last 2 y, which will help us to identify useful biomarkers from complex big data and provide a basis for precise medicine for malignant tumors.

The 2021 World Health Organisation classification of lung adenocarcinoma is based on the predominance and percentage of high-grade histological patterns, e.g. solid and micropapillary patterns, determined by semiquantitative estimation. Digital pathology can be used to evaluate the area of each pattern and calculate the exact percentage. To evaluate the prognostic predictive ability of a histological model for invasive non-mucinous adenocarcinoma using digital pathology. This retrospective cohort study included 76 patients with invasive non-mucinous lung adenocarcinoma who underwent lung resection at Songklanagarind Hospital between January 2010 and December 2016. The histological pattern area was measured on a digital slide using the QuPath Open software version 0.3.2. Clinical and pathological data, including the presence of tumour spread through airspaces, tumour necrosis, tumour-infiltrating lymphocytes, and lymphovascular invasion, were collected. The primary outcome was 5-year overall survival. The best model was provided by the Akaike information criterion, and the prognostic discrimination ability was compared with that of other models from previous studies by identifying the area under the curve (AUC) in the receiver operating characteristic analysis. The best model was validated using bootstrapping. The best model was a combination of stage and an 82 % cut-off high-grade pattern (AUC = 0.776). Tumours with ≥82 % high-grade pattern resulted in significantly worse prognoses (p = 0.001) than those with <82 % high-grade pattern. Our model had the highest AUC among all models from previous studies. This was validated using bootstrapping, with an AUC of 0.708. The best model for survival prediction was a combination of stage and an 82 % cut-off high-grade pattern.

The association between tumor-infiltrating lymphocytes and tumor immunity has long been recognized. Among T-cell types, CD45RO-positive memory T cells (CD45RO+) are reported to correlate with survival in several cancer types, but clinical evidence is lacking in esophageal squamous cell carcinoma (ESCC).

In surgical specimens from 162 preoperatively untreated patients, immunohistochemistry for CD45RO was performed to evaluate the density of CD45RO+ in the tumor core (CT) and invasive margin (IM) using an auto-count method. Patients were classified into high- versus low-CD45RO+ groups based on CD45RO+ density in CT and IM separately and combined. The relationship between CD45RO+ density and clinicopathological factors, including prognosis, was evaluated.

Average CD45RO+ density was 133/mm2 in CT and 372/mm2 in IM. No significant differences in clinicopathological factors according to high- versus low-CD45RO+ scores were identified. Using CT scores, the CD45RO+-high group had a better 5-year overall survival (OS) rate (77.2% vs. 54.7% CD45RO+-low, P = 0.0433), but OS rates did not differ statistically between the two groups by IM scores (75.7% vs. 50.3%, P = 0.0576). Using immunohistochemical scores for CT+IM, the survival difference was significant, with a 5-year OS rate of 73.7% for the CD45RO+-high group versus 46.3% for the CD45RO+-low group (P = 0.0141). Multivariate analysis identified CD45RO+ CT+IM density as an independent prognostic variable in OS (hazard ratio 2.27, 95% confidence interval 1.43-3.62, P = 0.0006).

Density of CD45RO+ expression in the CT and IM might be a predictor of long-term survival in ESCC.

The frequency of CTNNB1 mutation, one of the most frequent genetic events in hepatocellular carcinoma (HCC), is lower in Asian countries and in hepatitis B virus (HBV)-related HCCs. In this study, we evaluated the prevalence and types of CTNNB1-mutation in HBV-related HCC and correlated the molecular status with the histomorphological and immunohistochemical features.

A total of 108 consecutive cases of treatment-naïve, surgically resected HBV-related HCCs were selected. Targeted sequencing for CTNNB1 exons 3, 7 and 8 was performed, and the results were correlated with the expression pattern of glutamine synthetase (GS), nuclear β-catenin expression status and the histomorphological characteristics of the tumour. CTNNB1 mutations were identified in 13% of HBV-related HCCs; of these cases, mutations were found in D32-S37 (7%), T41 (4%) and S45 (2%) of exon 3. None of the HCCs demonstrated alterations in exons 7 and 8. CTNNB1 mutation was strongly associated with diffuse strong GS expression (P < 0.001), nuclear β-catenin expression (P < 0.001) and the classic CTNNB1 morphology (P = 0.038). Diffuse strong GS expression was observed in 78.6% of the CTNNB1-mutated HCCs, and nuclear β-catenin expression was identified in 64.3% of these cases. The classic CTNNB1 morphology was observed in 57% of all CTNNB1-mutated HCCs. Furthermore, programmed death-ligand 1 (PD-L1) was less frequently expressed in HCCs with classic CTNNB1 morphology.

CTNNB1 mutation was observed in 13% of HBV-related HCCs in this Korean cohort, and was associated with diffuse strong GS expression, nuclear β-catenin expression and classic CTNNB1 morphology.

Neoantigen vaccines are under investigation for various cancers, including epidermal growth factor receptor (EGFR)-driven lung cancers1,2. We tracked the phylogenetic history of an EGFR mutant lung cancer treated with erlotinib, osimertinib, radiotherapy and a personalized neopeptide vaccine (NPV) targeting ten somatic mutations, including EGFR exon 19 deletion (ex19del). The ex19del mutation was clonal, but is likely to have appeared after a whole-genome doubling (WGD) event. Following osimertinib and NPV treatment, loss of the ex19del mutation was identified in a progressing small-cell-transformed liver metastasis. Circulating tumour DNA analyses tracking 467 somatic variants revealed the presence of this EGFR wild-type clone before vaccination and its expansion during osimertinib/NPV therapy. Despite systemic T cell reactivity to the vaccine-targeted ex19del neoantigen, the NPV failed to halt disease progression. The liver metastasis lost vaccine-targeted neoantigens through chromosomal instability and exhibited a hostile microenvironment, characterized by limited immune infiltration, low CXCL9 and elevated M2 macrophage levels. Neoantigens arising post-WGD were more likely to be absent in the progressing liver metastasis than those occurring pre-WGD, suggesting that prioritizing pre-WGD neoantigens may improve vaccine design. Data from the TRACERx 421 cohort3 provide evidence that pre-WGD mutations better represent clonal variants, and owing to their presence at multiple copy numbers, are less likely to be lost in metastatic transition. These data highlight the power of phylogenetic disease tracking and functional T cell profiling to understand mechanisms of immune escape during combination therapies.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive subtype of non-Hodgkin's lymphoma that arises from the germinal center. It represents a heterogeneous disease characterized by different pathological, clinical, and molecular entities. Gene expression profiling based on the alleged cell of origin differentiates transcriptional subtypes such as germinal center and activated B cell-like. DLBCL accounts for around 40% of all non-Hodgkin's lymphomas worldwide. Its incidence generally increases with age. The international prognostic index remains the most important tool for disease stratification.The diagnosis of DLBCL is best made through an excisional biopsy of a suspicious lymph node. Nowadays, advanced techniques are employed to accurately diagnose and determine the clinical outcomes of patients. Immunohistochemistry, next-generation sequencing, and array-based comparative hybridization facilitate the global identification of diverse and numerous genetic alterations. However, further validation should be necessary to apply advanced techniques in clinical practice. In this review, we summarize the current literature and discuss the pathophysiology, epidemiology, and diagnostic advancements of DLBCL.

Pathological complete response (pCR) after neoadjuvant chemoimmunotherapy (NACi) is associated with improved patient outcomes in early triple-negative breast cancer (TNBC). This study aimed to identify factors associated with pCR after NACi. This cohort included all patients with stage II-III TNBC treated with NACi who underwent surgery at Institut Curie hospitals between 08/2021-06/2023. Among 208 patients, the overall pCR rate was 70% and was similar in ER < 1% (69%) and ER-low TNBC (73%, p = 0.6). In a multivariate model, Ki-67 ≥ 30% (OR 5.19 [1.73-17.3]), centralized TILs ≥ 30% (OR = 3.08 [1.42-7.04]), absence of DCIS at initial biopsy (OR = 2.56 [1.08-6.25]) and germline mutations in homologous recombination genes (OR = 9.50 [2.37-67.7]) remained strong independent predictors of pCR. These findings may guide treatment decisions in patients with TNBC undergoing NACi. Almost all patients with germline mutations in HR genes achieved pCR, supporting de-escalation trials. We suggest that ER-low tumors should be managed as TNBC tumors.

Sarcopenia and obesity are indicators for poor outcomes in colon cancer. Additionally, aggressive histopathologic tumor stromal features, such as a low tumor-stroma ratio (TSR) and low tumor-infiltrating lymphocytes (TILs) predict survival and treatment response. As their relationship remains underexplored, we studied the association between skeletal muscle mass, visceral adipose tissue (VAT), TSR, and TILs in patients with colon cancer.

We studied 194 stage II/III colon carcinoma patients who underwent elective surgery. Preoperative computed tomography (CT) scans classified patients into four groups based on skeletal muscle index (normal/low) and visceral adipose tissue index (normal/high). Tumor tissues were assessed for TSR and TILs, and five-year disease recurrence and relative hazard were evaluated.

Among the patients, 56 (28.9 %) were classified as Normal Muscle, Normal VAT, 26 (13.4 %) as Normal Muscle, High VAT, 75 (38.7 %) as Low Muscle, Normal VAT, and 37 (19.1 %) as Low Muscle, High VAT. Patients with low skeletal muscle mass were more often male (62.5 % vs. 39 %, P = 0.005). Stroma-high tumors were less common in Low Muscle, Normal VAT patients (24 %) compared to Normal Muscle, High VAT (50 %), Low Muscle, High VAT (48.6 %), and Normal Muscle, Normal VAT (41.1 %) patients (P = 0.020). Tumors with low TILs were similarly distributed across groups (P = 0.679). Low Muscle, Normal VAT patients had a lower recurrence hazard compared to both Low Muscle, High VAT (hazard ratio [HR] 0.34, 95 % CI 0.12-0.98, P = 0.048) and Normal Muscle, Normal VAT (HR 0.31, 95 % CI 0.11-0.87, P = 0.027) patients.

Low Muscle, Normal VAT colon cancer patients exhibited fewer aggressive tumor features and a lower recurrence risk compared to Low Muscle, High VAT patients. These findings highlight the importance of body composition in tumor biology and prognosis.

Head and neck squamous cell carcinomas (HNSCC) pose significant clinical challenges, particularly in high-risk cases with positive lymph node status. Current prognostic biomarkers are often costly and methodologically demanding. In this regard, histomorphological biomarkers such as tumor buds (TB) and poorly differentiated clusters (PDC) represent promising, cost-effective prognostic indicators that are relatively straightforward to implement.

The prognostic significance of TB and PDC, in conjunction with stromal tumor-infiltrating lymphocytes (sTILs) and the tumor-stroma ratio (TSR), was evaluated in a cohort of 50 high-risk, nodal-positive HNSCC patients. Histomorphological features were assessed using standard hematoxylin and eosin (H&E) staining, while HPV association and PD-L1 expression were determined by means of immunohistochemistry (IHC) and/or PCR. All variables collected were subsequently correlated with traditional histopathological and clinical parameters. Finally, a novel scoring system incorporating TB and PDC was developed, and its association with overall survival (OS) was analyzed.

TB and PDC both demonstrated a significant impact on patients' OS (TB Log-rank test, p = 0.0499, PDC Log-rank test, p = 0.0235). A novel scoring system based on these features had strong association with patients' OS (Log-rank test, p = 0.0200) in contrast to the conventional and routinely performed grading system, which evaluates the degree of differentiation within neoplastic cells (Log-rank test, p = 0.3325). PD-L1 expression was not associated with TB and PDC formation. HPV-negative status was associated with a higher number of tumor buds.

This study reveals the potential prognostic value of TB and PDC in high-risk HNSCC, which may offer a practical and cost-effective alternative to traditional markers. Our proposed practicable and straightforward employable scoring system significantly correlates with OS, suggesting its potential benefit in clinical practice. These findings advocate for further validation to enhance prognostic accuracy and guide treatment strategies in HNSCC.

Evaluation of the prognostic impact of tumor microenvironment (TME) has received attention in recent years. We introduce a TME-based risk stratification for oropharyngeal squamous cell carcinoma (OPSCC).

A total of 182 patients treated for OPSCC at the Helsinki University Hospital were included. TME-based risk stratification was designed combining tumor-stroma ratio and stromal tumor-infiltrating lymphocytes assessed in hematoxylin and eosin-stained sections.

In multivariable analysis, TME-based risk stratification associated with poor disease-free survival with a hazard ratio (HR) of 2.68 (95% CI 1.11-6.48, p = 0.029). In addition, the proposed risk stratification was associated with poor disease-specific survival (HR 2.687, 95% CI 1.28-5.66, p = 0.009) and poor overall survival (HR 2.21, 95% CI 1.23-3.99, p = 0.008).

Our TME-based risk stratification provides a powerful prognostic tool that can be used in daily treatment planning of OPSCC together with tumor-related prognostic markers.

We aimed to validate the prognostic significance of tumor budding (TB) in p16-positive oropharyngeal squamous cell carcinomas (OPSCC).

We analyzed digitized H&E-stained slides from a multicenter cohort of five large university centers consisting of n = 275 cases of p16-positive OPSCC. We evaluated TB along with other histological parameters (morphology, tumor-stroma-ratio, lymphovascular invasion (LVI), perineural invasion) and calculated survival outcomes using both univariate and multivariate analyses.

TB was identified as an independent prognostic parameter, with TB-high cases showing inferior outcomes in univariate (HR: 3.08, 95%-CI: 1.71-5.54) and multivariate analyses (HR: 4.03, 95%-CI: 1.65-9.83). Similarly, LVI remained an independent prognostic factor (HR: 3.00, 95%-CI: 1.22-7.38). A combined classification including TB and LVI stratified cases into low-, intermediate- and high-risk categories. We could not detect correlations between TB and the number of lymph node metastases or between TB and an extracapsular extension of lymph node metastases.

In addition to LVI, we could identify TB as an independent prognostic factor in p16-positive OPSCC in this multicenter study cohort. Thus, evaluating TB along with LVI in a combined scheme for prognostication might help to establish a more personalized treatment regimen for patients with p16-positive OPSCC.

Background: Tumor-infiltrating lymphocytes (TILs) are a protective prognostic factor in several solid tumors and predict response to immune checkpoint inhibitor therapy. The prognostic impact of TILs in medullary thyroid cancer (MTC) is poorly understood. Materials and Methods: In this retrospective cohort study, we assessed the TILs profile of primary MTC tumors using the International TILs Working Group system and correlated this with clinicopathological prognostic variables, including the International Medullary Thyroid Cancer Grading System (IMTCGS) grade and survival outcomes. Results: We identified 71 patients with primary MTC tumors who were treated surgically between 1995 and 2016 at the Royal North Shore Hospital in Sydney, Australia. The median (interquartile range) duration of follow-up was 69 (90) months. Using the ITWG system, all patients with MTC had low TILs, with a median (range) of 3% (0-10%). This group was further subdivided into "very low" (0-4%) and "low" (5-10%), and on Cox regression analysis, increasing TILs were associated with increased local recurrence (log-rank p = 0.022, odds ratio [OR] 1.94 [confidence interval or CI 0.61-6.16], p = 0.26), reduced disease-specific survival (log-rank p = 0.015, OR 5.11 [CI 1.01-26.0], p = 0.049), and a trend to decreased distant metastasis-free survival (log-rank p = 0.14). When examining the association between TILs and other prognostic factors, only "high IMTCGS grade" was significantly associated with increased TILs (OR 7.29 [CI 1.21-43.90], p = 0.015). In the multivariable logistic regression analysis, there was no significant association between TILs and local recurrence or disease-specific survival. Conclusions: In our study, the prognostic value of TILs in MTC was limited. Even high-grade MTC can be considered an immune quiescent tumor, and the adverse prognostic factors associated with higher grade tumors outweigh the marginal increase in immune recognition associated with a slight increase in TILs. The low level of TILs in MTC and their lack of correlation with survival suggest that immune checkpoint inhibitor therapy may not be effective.

To correlate between immunohistochemical expression of tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and natural killer (NK) cells with the AJCC 8th edition TNM staging system and other disease-modifying clinico-pathological variables.

The representative histology sections of tumor invasive margin (IM) and tumor core (TC) were selected according to the International Immuno-Oncology Biomarker Working Group and were subjected to immunohistochemistry with antibodies for TILs (CD3, CD8, FOXP3), NK Cells (CD57), TAMs (CD68, CD163) and pan-leukocyte marker (CD45). Histo-immuno-density-intensity (HIDI) scoring was calculated as a product of the proportion and intensity of staining. Ordinal-ordinal and continuous-ordinal variables were correlated using Kendall's tau-b (τb), and binary-ordinal variables were correlated using Rank-Biserial (rrb) statistics.

A total of 111 patients were included in the study. None of the clinical and pathological parameters showed a strong correlation with any of the immune infiltrates including TNM staging.

We hypothesize an independent activity of tumor immunology in the disease prognosis.

CTRI/2020/07/026335.

Background: The aim of this study was to evaluate biomarkers and biological characteristics of tumor biopsies from patients with head and neck cancer (HNC) to assess the risk of early death. Furthermore, we analyzed whether any combination of markers could be used for the prognostication of death within six months after cancer diagnosis. Materials and Methods: Patients diagnosed with HNC, receiving curative treatment decision at a multidisciplinary tumor board meeting, and who died within six months of diagnosis were included in this study. Nine patients who died within six months from diagnosis were identified and matched according to the tumor site and stage to seventeen patients who survived for at least two years. Results: The expression of markers was compared between the early-death patients and survivors. There was significantly higher Ki-67 expression in patients who died within six months than in those surviving for two years, with a mean difference of 21% (p = 0.038). A significant difference in cytoplasmic survivin expression was noted where early-death patients had increased expression compared to the survivors (p = 0.021). Furthermore, the intensity of survivin staining differed between the groups (p = 0.006). Conclusions: The results of this pilot study indicate that Ki67 and survivin could be potential prognostic biomarkers for early death in patients with HNC and possibly included in a panel of prognostic markers of value for treatment decision making.

The tumor microenvironment plays a critical role in cancer progression and therapeutic responsiveness, with the tumor immune microenvironment (TIME) being a key modulator. In head and neck squamous cell carcinomas (HNSCCs), immune cell infiltration significantly influences the response to radiotherapy (RT). A better understanding of the TIME in HNSCCs could help identify patients most likely to benefit from combining RT with immunotherapy. Standardized, cost-effective methods for studying TIME in HNSCCs are currently lacking. This study aims to leverage deep learning (DL) to quantify immune cell densities using immunohistochemistry in untreated oropharyngeal squamous cell carcinoma (OPSCC) biopsies of patients scheduled for curative RT and assess their prognostic value. We analyzed 84 pretreatment formalin-fixed paraffin-embedded tumor biopsies from OPSCC patients. Immunohistochemistry was performed for CD3, CD8, CD20, CD163, and FOXP3, and whole slide images were digitized for analysis using a U-Net-based DL model. Two quantification approaches were applied: a cell-counting method and an area-based method. These methods were applied to stained regions. The DL model achieved high accuracy in detecting stained cells across all biomarkers. Strong correlations were found between our DL pipeline, the HALO Image Analysis Platform, and the open-source QuPath software for estimating immune cell densities. Our DL pipeline provided an accurate and reproducible approach for quantifying immune cells in OPSCC. The area-based method demonstrated superior prognostic value for recurrence-free survival, when compared with the cell-counting method. Elevated densities of CD3, CD8, CD20, and FOXP3 were associated with improved recurrence-free survival, whereas CD163 showed no significant prognostic association. These results highlight the potential of DL in digital pathology for assessing TIME and predicting patient outcomes.

Adoptive cell therapy (ACT) utilizing tumor-infiltrating lymphocytes (TILs) has emerged as a successful treatment modality for various malignancies. However, TILs cultured from colorectal cancer (CRC) liver metastasis remain underexplored. Fifteen CRC liver metastasis tissues underwent initial expansion (IE) of TILs and rapid expansion (REP). Histologic examination including the level of stromal TILs and Klintrup-Mäkinen score, were assessed by pathologists and deep learning-derived spatial analysis. We performed correlation analysis between expanded TILs and histopathologic factors. All cases exhibited successful IE, with a mean IE TIL count per fragment and total IE TIL per case of 2.59 ± 2.79e5 cells and 167.79 ± 126.97e5 cells, respectively. Five cases underwent REP, with a median fold change of 3,610 (range, 1,136-4,925). The median CD4+/CD8 + ratio in IE TILs and REP TILs were 3.66 and 0.68, respectively. A significant correlation was observed between the mean number of expanded TILs per fragment and KM score (p = 0.022). Successful expansion of TILs from CRC liver metastasis was achieved. Assessment of KM score may serve as a predictive tool for the obtainable TILs before IE. These findings lay the groundwork for future studies to establish effective ACT in patients with metastatic CRC.

Melanoma is an aggressive form of skin cancer in which tumor-infiltrating lymphocytes (TILs) are a biomarker for recurrence and treatment response. Manual TIL assessment is prone to interobserver variability, and current deep learning models are not publicly accessible or have low performance. Deep learning models, however, have the potential of consistent spatial evaluation of TILs and other immune cell subsets with the potential of improved prognostic and predictive value. To make the development of these models possible, we created the Panoptic Segmentation of nUclei and tissue in advanced MelanomA (PUMA) dataset and assessed the performance of several state-of-the-art deep learning models. In addition, we show how to improve model performance further by using heuristic postprocessing in which nuclei classes are updated based on their tissue localization.

The PUMA dataset includes 155 primary and 155 metastatic melanoma hematoxylin and eosin-stained regions of interest with nuclei and tissue annotations from a single melanoma referral institution. The Hover-NeXt model, trained on the PUMA dataset, demonstrated the best performance for lymphocyte detection, approaching human interobserver agreement. In addition, heuristic postprocessing of deep learning models improved the detection of noncommon classes, such as epithelial nuclei.

The PUMA dataset is the first melanoma-specific dataset that can be used to develop melanoma-specific nuclei and tissue segmentation models. These models can, in turn, be used for prognostic and predictive biomarker development. Incorporating tissue and nuclei segmentation is a step toward improved deep learning nuclei segmentation performance. To support the development of these models, this dataset is used in the PUMA challenge.

We focused on how the immunophenotypes based on the distribution of CD8-positive tumor-infiltrating lymphocytes (TILs) relate to the endometrial cancer (EC) molecular subtypes and patients' prognosis.

Two cohorts of EC patients (total n = 145) were analyzed and categorized using the Molecular Risk Classifier for Endometrial cancer (ProMisE): POLEmut (POLE mutation), MMRd (mismatch repair deficiency), NSMP (no specific molecular profile), and p53abn (p53 abnormality). CD8-positive TILs, within the central tumor and the invasive margin, were examined by using immunohistochemical staining and advanced image-analysis software. It was investigated whether these immunophenotypes correlate with the molecular subtypes and patients' survival. RNA-sequencing (RNA-seq) was used to explore tumor-derived factors influencing these immunophenotypes.

Three distinct immunophenotypes (inflamed, excluded, and desert) based on the CD8-positive TIL patterns were identified in EC patients. Notably, the inflamed phenotype was most frequently observed in the POLEmut and MMRd subtypes, while the desert phenotype was predominant in the NSMP subtype; however, other immunophenotypes were also observed. All p53abn subtype showed the non-inflamed (excluded or desert) phenotype. The prognosis was markedly poorer in the patients with the non-inflamed phenotype than in those with the inflamed phenotype. The RNA-seq analysis showed that the expression of MYC target genes and type-1 interferon response genes was enriched in the non-inflamed phenotype in MMRd and NSMP subtypes, respectively.

Evaluating not only the molecular classification but also the immunophenotype may lead to more personalized immunotherapy in EC and elucidating the mechanisms that underlie the formation of the three immunophenotypes could lead to the discovery of new immunotherapy targets.

EP300 mutation is common in esophageal squamous cell carcinoma (ESCC). We aimed to analyze the influence of EP300 mutation on treatment effect and prognosis in ESCC patients underwent neoadjuvant chemoradiotherapy.

Thirty ESCC patients treated with neoadjuvant chemoradiotherapy (nCRT) were enrolled in this study. After assessment of treatment response, transcriptome analyses and immunochemistry were performed for cases in well response or poor response group.

Four of thirty patients harbor EP300 mutation and have poor response to nCRT. Of the remaining 26 nonmutated patients, fifteen patients have a well response, and seven patients have a poor response to nCRT. The EP300-mutated poor response cases have significantly higher immune score than EP300 wild-type poor response cases (P = 0.002), but have no difference from EP300 wild-type well response cases (P = 0.360). Up-regulated B cell related pathways and more CD20 + B cells are in EP300-mutated poor response group, when compared with EP300 wild-type poor response group (P < 0.050). Whereas up-regulated negative regulation of cell death related pathway and higher bcl2 expression level was observed in EP300 mutated poor response group than these in EP300 wild-type well response group (P < 0.050). In prognosis, cases in EP300-mutated poor response group have worse disease-free survival (P = 0.019) and overall survival (P = 0.004) than EP300 wild-type well response group.

EP300 mutated cases have high immune activity in tumor microenvironment. The high anti-apoptosis activity of tumor cells may contribute to resistance to nCRT in EP300-mutated cases.

There is lack of knowledge on the utility of prognostic histopathologic characteristics in adenoid cystic carcinoma (ACC) of the head and neck. We evaluated the prognostic value of tumor and stroma-related histopathologic features in ACC.

A total of 65 cases of ACC from minor and major salivary glands were included in this study. We evaluated tumor budding, tumor-infiltrating lymphocytes (TILs), and tumor-stroma ratio (TSR) in hematoxylin and eosin (HE) stained sections.

Stroma-rich ACCs recurred more frequently (p = 0.029) during follow-up and associated with distant metastasis (p = 0.038). In multivariable analysis, stroma-rich tumors associated with poorer disease-specific survival with a hazard ratio of 3.76 (95% CI 1.10-12.83, p = 0.034). ACCs commonly showed a low infiltration of TILs as 89% of the tumors was characterized by an immune desert pattern. Low infiltration of TILs associated significantly with increased tumor budding (p = 0.039).

Adverse features of TSR and tumor budding are widely expressed in ACC, and stroma-rich tumors are associated with poor prognosis. Low number of TILs in ACC tissue indicates a weak immune response by the host and illustrates the nature of ACC as a relentless malignancy.

Ovarian clear cell carcinoma (OCCC) has a high incidence in Asia, with a frequent occurrence at an early stage, but without sufficient data on molecular stratification for high-risk patients. Recently, immune-hot features have been proposed as indicators of poor prognosis in early stage OCCC. Specific patterns of intratumoral heterogeneity associated with immune-hot features must be defined. NanoString Digital Spatial Profiling technology (Cold spring biotech corp.) was used to decipher the spatial distribution of the 18-plex protein panel. Regions of interest (ROIs) were collected based on the reference hematoxylin and eosin-stained morphology. Areas of illumination (AOIs) were defined according to the ROI segmentation using the fluorescence signals of the visualization markers pan-cytokeratin (PanCK), CD45, or DNA. Unsupervised hierarchical clustering of 595 AOIs from 407 ROIs showed that the PanCK segments expressed different combinations of immune markers, suggestive of immune mimicry. The following 3 immune-hot clusters were identified: granzyme B-high, immune signal-high , and immune-like cells; the following 2 immune-cold clusters were identified: fibronectin-high and immune checkpoint-high cells. In tumor samples at the International Federation of Gynecology and Obstetrics stage IC1/2 experiencing recurrence, there was an increased occurrence of PanCK+ AOIs with immune signal-high and immune-like cell groups in the papillary morphology surrounded by macrophage lineage tumor-infiltrating immune cells (TIIs). In contrast, for tumor samples at the International Federation of Gynecology and Obstetrics stage IC3/II with recurrence, PanCK+ AOIs were prevalent in the fibronectin-high group, particularly in those with a tubulocystic morphology surrounded by lymphoid lineage non-TIIs. Our study on the spatial profiling of early stage OCCC tumors revealed that the immune mimicry of tumor cells, presence of TIIs, and morphologic patterns were associated with recurrence, which switched during tumor progression.

The tumor immune microenvironment is increasingly becoming a key consideration in developing treatment regimens for aggressive cancers, with evidence that regulatory T cells (Tregs) attenuate the antitumor response by interrupting cytotoxic T cells (CD8+). Here, we hypothesized the prognostic relevance of the proportions of Tregs (marked by forkhead box protein 3 [FOXP3]) and CD8+ cells in diffuse, non-Epstein-Barr virus (EBV)/non-microsatellite instability (MSI)-high gastroesophageal adenocarcinomas (GEAs), which are clinically characterized as more aggressive, immunologically inactive tumors as compared with their intestinal counterparts. Cell-count ratios of FOXP3+/CD8+ expression were calculated at the intratumoral region and invasive margin discretely on digital images from 303 chemo-naive non-EBV/non-MSI-high esophagogastric junction (EGJ) adenocarcinomas. A significant modifying prognostic effect of tumor histology was observed between 5-year EGJ cancer-specific survival and the FOXP3+/CD8+ ratio at the invasive margin in pStage I-III tumors (p for interaction = 0.022; hazard ratio [HR] = 8.47 and 95% confidence interval [CI], 2.04-35.19 for high ratio [vs. low] for diffuse; HR = 1.57 and 95% CI, 0.88-2.83 for high ratio [vs. low] for intestinal). A high FOXP3+/CD8+ ratio at the invasive margin was associated with RUNX3 methylation (p = 0.035) and poor prognosis in RUNX3-methylated diffuse histological subtype (5-year EGJ cancer-specific survival, 52.3% for high and 100% for low, p = 0.015). Multiomics data from The Cancer Genome Atlas linked CCL28 with RUNX3-suppressed diffuse histological subtypes of non-EBV/non-MSI-high GEA. Our data suggest that a high FOXP3+/CD8+ ratio at the invasive margin might indicate tumor immune escape via CCL28, particularly in the RUNX3-methylated diffuse histological subtype.

Differences in the immune microenvironment and responses to immunotherapy may exist between primary non-small cell lung cancer (NSCLC) and brain metastases (BMs). This study aimed to investigate discrepancies in programmed death-ligand 1 (PD-L1) expression, tumor-infiltrating lymphocytes (TILs), tertiary lymphoid structures (TLS), and tumor mutational burden (TMB) between matched BMs and primary tumors (PTs) in NSCLC.

Twenty-six pairs of surgically resected BMs and corresponding PTs from NSCLC patients were collected. PD-L1 expression and TILs, including CD8, CD3, CD4, CD20, CD68, and CD21, were analyzed using immunohistochemistry (IHC) and quantitatively assessed through digital image analysis. Whole-exome sequencing (WES) was performed to investigate genomic discrepancies and variations in TMB.

The density of PD-L1+ cells did not differ significantly between matched PTs and BMs (P>0.99). However, BMs exhibited a higher tumor proportion score (TPS) compared to PTs (mean TPS: 31.92% vs. 25.96%, P=0.049), with moderate agreement in categorized TPS (κ=0.653). Analysis of TILs revealed a significant reduction in CD3+ T cells (P<0.001), CD8+ cytotoxic T cells (P<0.001), CD20+ B cells (P<0.001), and CD68+ macrophages (P=0.02) in BMs compared to PTs. BMs also exhibited a loss of TLS, with no presence of mature TLS marked by CD21 expression. The number of non-synonymous mutations was generally higher in BMs than in PTs, with only 34.69% of mutations shared between paired PTs and BMs. TMB was slightly increased in BMs (mean TMB: 34.2 mutations/Mb in BMs vs. 26.8 mutations/Mb in PTs; P=0.30). Additionally, the log-rank test indicated that a higher density of CD20+ B cells in BMs was significantly associated with better overall survival (P=0.007).

Compared to primary NSCLC tumors, matched BMs show an increase in TPS of PD-L1 expression and TMB, but a significant reduction in TILs and loss of mature TLS, suggesting an immune-suppressive microenvironment in BMs. The infiltration of CD20+ B cells may serve as a potential prognostic biomarker in NSCLC with BMs.

The success of immune checkpoint inhibitors (ICI) in melanoma therapy has catalyzed the introduction of ICI in increasingly early stages of the disease. This exposes many patients with a lower risk of relapse to the risk of protracted adverse events, highlighting the need for biomarkers guiding the use of ICI. Already many years ago, brisk infiltration of primary melanomas by lymphocytes has been linked to improved patient outcome, but controversial findings due to a high variability in classification systems have been described CD8+ T cells have been identified as a primary mediator of antitumor immunity in patients treated with ICI. As CD8+ T cells require the presentation of antigens via MHC-I on target cells, downregulation and loss of MHC-I have been observed as resistance mechanisms to ICI. In this study, we revisit the role of MHC-I expression and CD8+ T-cell infiltration in melanoma evolution using a cohort of advanced primary and matched metastatic melanomas by using an automated immunohistochemistry and digital pathology workflow. Our results show that downregulation of MHC-I expression is a frequent event in advanced primary melanomas that is associated with decreased CD8+ T-cell infiltration and an early metastatic spread to sentinel lymph nodes. Furthermore, MHC-I downregulation and decreased infiltration with CD8+ T cells are also associated with resistance to ICI. Our results suggest that analyses of MHC-I expression and CD8+ T-cell infiltration patterns could serve as future biomarkers to guide the decision to treat patients in early stages of melanoma with ICI.

Malignant melanoma, the most aggressive form of skin cancer, is characterized by unpredictable growth patterns, and its mortality rate has remained alarmingly high over recent decades, despite various treatment approaches. One promising strategy for improving outcomes in melanoma patients lies in the early use of biomarkers to predict prognosis. Biomarkers offer a way to gauge patient outlook early in the disease course, facilitating timely, targeted intervention. In recent years, considerable attention has been given to the immune response's role in melanoma, given the tumor's high immunogenicity and potential responsiveness to immunologic treatments. Researchers are focusing on identifying predictive biomarkers by examining both cancer cell biology and immune interactions within the tumor microenvironment (TME). This approach has shed light on tumor-infiltrating lymphocytes (TILs), a type of immune cell found within the tumor. TILs have emerged as a promising area of study for their potential to serve as both a prognostic indicator and therapeutic target in melanoma. The presence of TILs in melanoma tissue can often signal a positive immune response to the cancer, with numerous studies suggesting that TILs may improve patient prognosis. This review delves into the prognostic value of TILs in melanoma, assessing how these immune cells influence patient outcomes. It explores the mechanisms through which TILs interact with melanoma cells and the potential clinical applications of leveraging TILs in treatment strategies. While TILs present a hopeful avenue for prognostication and treatment, there are still challenges. These include understanding the full extent of TIL dynamics within the TME and overcoming limitations in TIL-based therapies. Advancements in TIL characterization methods are also critical to refining TIL-based approaches. By addressing these hurdles, TIL-focused research may pave the way for improved diagnostic and therapeutic options, ultimately offering better outcomes for melanoma patients.

To assess the relation between immune microenvironment, survival, and clinicopathological characteristics.

This study was a retrospective, single-center, observational study. Patients with a vulvovaginal melanoma and available archived material were included. All cases underwent pathology review, tumor-infiltrating lymphocyte quantification, and next-generation sequencing analysis, when feasible. Clinical data included demographic, treatment, and prognostic data.

Forty-two patients were selected during the study period, but 13 were finally excluded owing to unavailable formalin-fixed, paraffin-embedded material or unknown follow-up data. Twelve of 19 cases (63.2%) had at least one genetic mutation, 3/18 (16.7%) had BRAF, 3/18 (16.7%) had c-KIT mutation, and 4/17 (23.5%) had NRAS mutations. High stromal tumor-infiltrating lymphocytes were identified in 13/28 patients (46.4%), and brisk tumor-infiltrating lymphocytes in 17/28 patients (60.7%). A density of stromal tumor-infiltrating lymphocytes >40% and brisk distribution were the single clinicopathologic factor associated with increased disease-free survival.

The study showed that brisk tumor-infiltrating lymphocytes and stromal tumor-infiltrating lymphocytes were a marker for disease progression, and for response to immunotherapy strategies. To validate these findings on a larger scale, further research is warranted through a multicenter study with a larger cohort and additional genetic and translational analysis.

The study investigated the expression of GATA3, a transcription factor involved in immune regulation, in tubo-ovarian carcinomas and its association with clinicopathological factors and prognosis. Immunohistochemical analysis was performed on 91 tubo-ovarian carcinoma samples to determine the presence of GATA3-positive inflammatory cells in the tumor microenvironment. A threshold of 10% or higher was considered a positive expression. The results showed that 46.7% of tubo-ovarian carcinomas exhibited positive expression of GATA3 in inflammatory cells. There was no significant difference in GATA3 expression between patients who received pre-surgical chemotherapy and those who underwent primary surgery. However, high-grade serous carcinomas had a significantly higher proportion of GATA3-positive inflammatory cells compared to other subtypes. Advanced-stage tumors (stage III) had a higher percentage of GATA3-positive inflammatory cells compared to stage II and I tumors. Patients with positive GATA3 expression had a significantly lower disease-free survival rate. However, there was no significant association between GATA3 expression and chemotherapy response score. These findings suggest that increased expression of GATA3 in mononuclear inflammatory cells is associated with higher grade, advanced stage, and increased risk of recurrence in tubo-ovarian carcinoma. This implies that heightened GATA3 expression negatively impacts anti-tumor immunity, tumor growth progression, and invasiveness in tubo-ovarian carcinomas.

The field of immunology is fundamental to our understanding of the intricate dynamics of the tumor microenvironment. In particular, tumor-infiltrating lymphocyte (TIL) assessment emerges as essential aspect in breast cancer cases. To gain comprehensive insights, the quantification of TILs through computer-assisted pathology (CAP) tools has become a prominent approach, employing advanced artificial intelligence models based on deep learning techniques. The successful recognition of TILs requires the models to be trained, a process that demands access to annotated datasets. Unfortunately, this task is hampered not only by the scarcity of such datasets, but also by the time-consuming nature of the annotation phase required to create them. Our review endeavors to examine publicly accessible datasets pertaining to the TIL domain and thereby become a valuable resource for the TIL community. The overall aim of the present review is thus to make it easier to train and validate current and upcoming CAP tools for TIL assessment by inspecting and evaluating existing publicly available online datasets.

Previous breast carcinoma studies focused on the evaluation of tumour-infiltrating lymphocytes (TILs) or of tumoural stroma via the tumour stroma ratio (TSR). Few studies assessed peritumoural lymphocytes and almost no studies investigated a possible relationship between lymphocytes and stroma. This prompted us to evaluate the amount of tumour cells, intra- and peritumoural lymphocytes, and stroma in breast cancer to support the hypothesis that the stroma may block the infiltration of lymphocytes inside the tumour.

We collected a retrospective series of 158 breast cancers (<25 mm). In addition to standard TILs and TSR evaluations, we assessed the percentages of tumour cells, stromal myofibroblasts, intra- and peritumoural lymphocytes on full-section tumours with haematoxylin and eosin and immunohistochemical staining.

We showed significant negative correlations between the amounts of stroma and both intra- and peritumoural lymphocyte percentages. Considering the estrogen receptor positive invasive breast cancer of no special type cases, we showed that TSR had a positive prognostic value with an optimal threshold of 10 %.

This study is one of the first to show inverse correlations between tumoural stroma amount and intra- and peritumoural lymphocyte percentages, which supports the hypothesis that tumoural stroma can prevent the recruitment of lymphocytes around and within the tumour.

(1) Background: The worldwide endometrial cancer (EC) incidence is rising, amongst others linked to obesity, type 2 diabetes mellitus (T2DM), and metabolic syndrome, possibly due to low-grade adipose tissue inflammation. We studied immune cell infiltration in the endometrium in relation to diagnosis and obesity. (2) Methods: A cohort was created (n = 44) from postmenopausal women, lean (n = 15) and obese (n = 29), with bleeding complaints due to EC (n = 18) or benign pathology (n = 26). Endometrial biopsies were used to study the immune microenvironment and stained for macrophages (CD68 and CD163), T-cells (CD3 and CD8), and NK-cells (CD56). (3) Results: Malignant samples showed reduced intraepithelial CD3+ and CD8+ T-cells and increased stromal CD3+ T-cells. In obese patients, increased intraepithelial CD3+ and CD8+ T-cells were detected, especially in obese patients with T2DM. Epithelial CD56+ NK-cells were depleted in EC; however, no effect of obesity on NK-cell infiltration was observed. Stromal CD68+ cells were reduced in EC patients, whereas the CD163+ cells were increased. (4) Conclusions: Obesity and malignancy are associated with differences in immune cell presence. The alterations in immune cell infiltration seen in obese EC patients with and without diabetes suggest a complex interaction where obesity-related low-grade inflammation plays a central role.

Current understanding of oral squamous cell carcinoma (OSCC) is incomplete with regard to prognostic factors that lead to the considerable heterogeneity in treatment response and patient outcomes. We aimed to evaluate the impact of individual tumour-infiltrating lymphocyte (TIL) subsets on prognosis as a possible rationale for this, in a retrospective observational study.

Immunohistochemistry was performed to quantitatively assess cell densities of CD3+, CD20+, CD4+, CD8+ and FOXP3+TIL subsets in 50 surgically treated OSCC cases. Results were correlated with disease-free survival (DFS) and overall survival (OS). Receiver operating characteristic curve analysis and Youden index were applied to determine prognostically significant cut-off values.

Mean counts for CD3+, CD4+, CD8+, CD20+ and FOXP3+TILs were 243, 52, 132, 53 and 116 cells per high power field, respectively. High CD8+ and low FOXP3+TIL counts, and high ratio of CD8:FOXP3 were significantly associated with longer DFS and OS, as well as with improved tumour-host interface parameters.

Host immune response and its interaction with cancer cells have a significant impact on OSCC outcomes, with some TIL subsets being more clinically relevant than others. High cytotoxic T-cell (CD8) and low Treg (FOXP3) counts, and high cytotoxic T-cell to Treg (CD8:FOXP3) ratio are significantly associated with favourable prognosis. These results may serve as a leading point in identifying novel therapeutic agents that can redesign the tumour immune microenvironment by reducing infiltrating FOXP3-lymphocytes, and modifying their signalling pathways.

Background: Glioblastoma IDH-wildtype (GBM IDH-wt) is the most aggressive brain tumor in adults and is characterized by an immunosuppressive microenvironment. Different factors shaping its tumor microenvironment (TME) regulate tumor progression and treatment response. The aim of this study was to characterize the main immunosuppressive elements of the GBM IDH-wt TME. Methods: Immunohistochemistry for CD3, CD4, CD8, CD163, programmed death ligand 1 (PD-L1) and programmed death 1 (PD1) was performed on surgical tumor specimens from patients diagnosed with GBM IDH-wt, according to the CNS WHO 2021 criteria. The impact of categorical variables on time-dependent outcomes such as overall survival (OS) and progression-free survival (PFS) has been estimated through the Kaplan-Meier method. Results: We included 30 patients (19 males and 11 females), median age of 59.8 years (range 40.2-69.1 years). All patients underwent surgery followed by temozolomide concurrent with and adjuvant to radiotherapy. MGMT was methylated in 14 patients (47%) and unmethylated in 16 patients (53%). The overall absolute percentages of CD4+ lymphocytes, both intratumoral and perivascular, were significantly more represented than CD8+ lymphocytes in the TME (p = 0.02). A low density of CD4+ lymphocytes (≤10%) was found to be a favorable prognostic factor for GBM outcome (p = 0.02). Patients with MGMT methylated and unmethylated tumors exhibited a distinct TME composition, with a significant higher number of perivascular CD8+ lymphocytes (p = 0.002), intratumoral CD8+ lymphocytes (p = 0.0024) and perivascular CD4+ lymphocytes (p = 0.014) in MGMT unmethylated tumors. PD-L1 expression in tumor cell surface was observed in four tumors (13.3%), and PD1 expression in infiltrating T lymphocytes was observed in nine (30%) tumors, with predominantly perivascular distribution. Conclusions: MGMT methylated and unmethylated tumors exhibit different immune profiles, likely reflecting the different biology of these tumors. The expression of PD-L1 in GBM IDH-wt patients is confined to a small subpopulation. While we found a significant association between low CD4+ lymphocyte density (≤10%) and survival, given the small numbers of our cohort, the prognostic value of CD4+ lymphocyte density will need to be validated in large-scale studies.

The spatial variability and clinical relevance of the tumor immune microenvironment (TIME) are still poorly understood for hepatocellular carcinoma (HCC). In this study, we aim to develop a deep learning (DL)-based image analysis model for the spatial analysis of immune cell biomarkers and microscopically evaluate the distribution of immune infiltration.

Ninety-two HCC surgical liver resections and 51 matched needle biopsies were histologically classified according to their immunophenotypes: inflamed, immune-excluded, and immune-desert. To characterize the TIME on immunohistochemistry (IHC)-stained slides, we designed a multistage DL algorithm, IHC-TIME, to automatically detect immune cells and their localization in the TIME in tumor-stroma and center-border segments.

Two models were trained to detect and localize the immune cells on IHC-stained slides. The framework models (i.e., immune cell detection models and tumor-stroma segmentation) reached 98% and 91% accuracy, respectively. Patients with inflamed tumors showed better recurrence-free survival than those with immune-excluded or immune-desert tumors. Needle biopsies were found to be 75% accurate in representing the immunophenotypes of the main tumor. Finally, we developed an algorithm that defines immunophenotypes automatically based on the IHC-TIME analysis, achieving an accuracy of 80%.

Our DL-based tool can accurately analyze and quantify immune cells on IHC-stained slides of HCC. Microscopic classification of the TIME can stratify HCC according to the patient prognosis. Needle biopsies can provide valuable insights for TIME-related prognostic prediction, albeit with specific constraints. The computational pathology tool provides a new way to study the HCC TIME.