Clinicopathological and radiological characteristics and prediction of survival in colon cancer

Abstract

There are various histological characteristics which have been proposed to predict the survival rate in colon cancer. However, there is no definitive model to accurately predict the survival. Therefore, it is important to find out one model for the prediction of survival in colon cancer which may also include the preoperative, and operative factors in addition to histopathology.

Key Words: Colon cancer; Survival; Predictors; Clinicopathological; Radiological

Core Tip: Although there are several prognostic predictors of colon cancer survival, there are none that are clinically useful. A nomogram developed from various clinical, radiological, and histological parameters can serve as a comprehensive and effective prognostic tool, which can assist clinicians in risk stratification and provide essential guidance for individualized treatment.

INTRODUCTION

The understanding of cancer, particularly colon cancer, has significantly advanced over the years, driven by breakthroughs in molecular genetics and improvements in preoperative diagnostic techniques such as histopathology and cross-sectional imaging[1]. Various prognostic and predictive biomarkers have been studied to provide insights into patient outcomes, including overall survival (OS) and relapse-free survival[2]. Prognostic markers offer treatment-independent prognostic information regarding patient survival, whereas predictive biomarkers, guide the therapy decisions based on treatment response in biomarker-positive patients compared to those who are biomarker-negative[3]. Currently, the prognosis of colon cancer primarily relies on the cancer stage as defined by the tumor-node-metastasis (TNM) staging classification[4]. The TNM staging system focuses on several clinicopathological features. There appears to be differences in survival patterns, which is not only dependent on stage, suggesting a complex interaction among stage, pathological features, molecular genetics and hence the prognosis[5,6]. Here we shall discuss various clinicopathological and radiological markers as a predictor of survival in colon cancer.

CLINICOPATHOLOGICAL DETERMINANTS

The clinical and pathological characteristics of a tumor are influenced by its molecular biology and play a synergistic role in determining OS. Young-onset-colon cancer (diagnosed before the age of 50) exhibits distinct molecular and genetic variations compared to older patients, resulting in more aggressive tumor behavior[7]. They are often associated with high-risk consensus molecular subtype and chromosomal instability. They typically display signet ring cell histology, presence of mucin, lymphovascular invasion (LVI), and perineural invasion (PNI), all of which are markers of poor prognosis and rapid progression[7,8]. Some authors attribute these characteristics to delayed diagnosis and advanced stage at presentation[9]. Despite aggressive treatment, the survival is poor and recurrence is very common[10,11]. Sex and race appear to have a minimal impact on prognosis. However, some studies suggest a poorer prognosis among men and individuals of Black race[12,13]. Considering tumor site, left-sided colonic cancer has a slightly better survival rate than right-sided colonic cancer[14].

The TNM classification system provides robust prognostic information, particularly for stages I and IV[13]. Stages II and III, however, exhibit greater heterogeneity[15]. As the T stage increases, so does the incidence of nodal and distant metastasis[16]. Recurrence-free survival is also affected by T stage. A significant increased risk of recurrence in T4 has been reported as compared to T3 tumors[17]. In colon cancer, the T stage does not account for tumor size, as size alone is not an independent prognostic factor[18]. The N stage, which indicates regional lymph node involvement, reduces the 5-year OS rate to 30%-60%, compared to 70%-90% in node-negative disease[19]. Fewer than 12 lymph nodes and a higher involved lymph nodes ratio (LNR) have poor prognosis[4]. There is currently no consensus on a cutoff value for high LNR, which may vary from 0.125 to 0.3 across different studies and guidelines[20]. Additionally, TNM staging does not incorporate LNR. The presence of distant metastasis remains the most significant predictor of outcomes, reducing the 5-year OS rate to less than 10%[21]. A perforated tumor presenting in the emergency department indicates disseminated disease, which is associated with a poor prognosis. In contrast, patients with acute obstruction are likely to have a reduced yield of lymph nodal[22].

Other histological determinants of prognosis are tumor budding, PNI, apical lymph node positivity, degree of differentiation, and tumor grade. Tumor budding, defined as the clustering of one to four tumor cells that dissociate from the invasive portion of a tumor, is an independent prognostic marker. It has been included in both the latest American Joint Committee on Cancer classification and the European Society for Medical Oncology guidelines. However, the National Institute for Health and Clinical Excellence guidelines do not yet recognize it as a high-risk feature[19]. PNI and LVI by tumor cells are means of tumor spread. PNI and LVI are often underreported by histopathologists, but have important prognostic significance. The presence of tumor cells in more than 33% of the nerve circumference surrounding tissues is defined as PNI. LVI is invasion of extramural veins and is an independent poor prognostic factor with an increased risk of hepatic metastasis. Tumor grade, or degree of differentiation, is an independent adverse prognostic factor, regardless of stage. It is typically defined by the percentage of gland formation, although the inclusion of cytological or other features in the grading assessment can vary. Involvement of apical lymph nodes, defined as lymph nodes located at the origin of the primary vessel supplying the tumor is another prognostic marker. The Japanese and Australian classification systems stage nodal metastasis based on tumor location and consider its involvement a poor prognosis[19].

Mutations in colon cancer influence the biological behavior of tumors, which in turn affects their response to chemotherapy and immunotherapy. Currently, due to insufficient evidence supporting their use for prognostication and the determination of adjuvant therapy, these mutations are primarily utilized in metastatic settings. For example, patients with Kirsten rat sarcoma viral oncogene homolog-mutated and v-Raf murine sarcoma viral oncogene homolog B1-V600E-mutated tumors are resistant to anti-epidermal growth factor receptor adjuvant therapy. Additionally, microsatellite instability-high tumors are immunogenic, making immunotherapy potentially beneficial in metastatic cases. Furthermore, resistance to 5-fluorouracil therapy has been observed in these patients[19].

RADIOLOGICAL DETERMINANTS

The radiological determinant of prognosis in colon cancer has not been studied as extensively as those in rectal cancer, where the role of magnetic resonance imaging is immense in treatment decision making and prognostication by predicting the circumferential resection margin and mesolectal involvement. Radiological imaging is effective in assessing the local extent of the disease and detecting metastases. Key prognostic factors on imaging include extramural extension of the primary tumor, bulky lymphadenopathy at the mesenteric root, ascites, extensive carcinomatosis, invasion into adjacent organs, and involvement of the retroperitoneal surgical margin[23-26].

Hu et al[27] presented a retrospective study involving 249 patients with colon cancer, aimed at developing a nomogram to predict OS based on computed tomography characteristics and clinicopathological factors. The patients were randomly divided into training and testing groups in a 1:1 ratio. The study identified lymph node metastasis on computed tomography, PNI, and tumor classification as independent prognostic factors. A nomogram incorporating these variables was constructed and validated, demonstrating strong predictive accuracy for OS probabilities at various time points. The inclusion of 12 computed tomography imaging characteristics further enhanced the accuracy of colon cancer prognosis predictions. The constructed nomogram exhibited high precision in predicting survival probabilities and can assist clinicians in formulating personalized treatment plans for patients with colon cancer. The model’s C-index values (0.804 for the training group and 0.692 for the testing group) indicated good discrimination, and the nomogram’s clinical benefits facilitate easy individualized survival prognosis predictions. However, further research with larger sample sizes and the inclusion of additional prognostic biomarkers is necessary to enhance the model’s effectiveness and comprehensiveness.

CONCLUSION

Colon cancer is heterogeneous in nature like other cancer and exhibits multiple clinicopathological and radiological features which may have great prognostic significance either in isolation or in association with factors that interact in complex ways to influence OS. A nomogram developed from these characteristics can serve as a comprehensive and effective prognostic tool. Furthermore, it can assist clinicians in risk stratification and provide essential guidance for the individualized treatment, postoperative monitoring and early detection follow up protocol in patients with colon cancer. A mathematical prognostic model, incorporating clinicopathological and radiological features is required for better prognostication, which has not yet been developed.