Mucinous Histology Might Be an Indicator for Enhanced Survival Benefit of Chemotherapy in Stage II Colon Cancer

Abstract

Background: It was a difficult question to identify candidates who would benefit most from adjuvant chemotherapy in stage II colon cancer because of the paucity of relevant conclusive clinical trial results. We aimed to assess if mucinous adenocarcinoma (MUA) could be an indicator for the efficacy of adjuvant chemotherapy in stage II colon cancer. Methods: Using SEER * Stat software V.8.3.5, eligible patients were then recruited from the SEER database. A χ 2 test was applied to compare the distribution of different categorical variables between nonmucinous adenocarcinoma (NMUA) and MUA groups. We then used the Kaplan-Meier method to analyze overall survival (OS) of different histological types in stage II colon cancer, and the log-rank test was then used to assess the OS differences. The Cox proportional regression risk models were also built in our analyses to eliminate potential crossed bias from other prognostic factors. Results: A total of 50,065 patients diagnosed with stage II colon cancer were recruited from the SEER database from 2004 to 2011; all the patients were divided into two groups, including NMUA (n = 44,785) and MUA (n = 5,280). The Cox analysis of the histological type indicated that the survival difference between MUA and NMUA failed to reach statistical significance in stage II colon cancer (P = 0.360). In NMUA, patients treated with adjuvant chemotherapy were independently associated with 37.2% decreased risk of overall mortality compared with those not [hazard ratio (HR) = 0.628, 95% confidence interval (CI) = 0.601-1.656, P < 0.001]; in MUA, the number increased to 41.5% (HR = 0.585, 95% CI = 0.515-0.665, P < 0.001). Conclusions: Our study showed that the survival difference between MUA and NMUA failed to reach statistical significance in stage II colon cancer. More importantly, our study had provided the first evidence that chemotherapy would offer higher survival improvement in MUA compared with NMUA in stage II colon cancer; mucinous histology might be an indicator for enhanced survival benefit of chemotherapy in stage II colon cancer.

Patients with Metachronous Peritoneal Metastatic Mucinous Colorectal Adenocarcinoma Benefit More from Cytoreductive Surgery (CRS) and Hyperthermic Intraperitoneal Chemotherapy (HIPEC) than Their Synchronous Counterparts

“…The neo/adjuvant treatment of MAC neoplasms is challenging: an impaired response to treatment and a shorter survival of patients is reported in most of the studies [ 22 , 24 , 33 ]. Some reports have suggested that the response to treatment in lower-stage MAC patients does not differ from that of non-MAC patients [ 34 , 35 ], but basically all of the studies agree that, in advanced stages, the therapy response of MAC is lower regardless the chemotherapy combination used [ 22 , 24 , 33 ]. Several novel therapeutic options have also emerged lately, including immunotherapies [ 22 , 24 ], drugs targeting mucins [ 36 ], and the possible use of nanoparticle drugs [ 22 ].…”

Prognostic significance of MUC2, CDX2 and SOX2 in stage II colorectal cancer patients

“…Several studies report that mucinous adenocarcinoma is more likely associated with advanced stages in CRC and less responsive to chemotherapy, comparing to non-mucinous adenocarcinoma [ 57 , 58 ]. The prognostic value of the mucinous histological subtype remains controversial, and some studies, including a very recently published large population-based study, disclosed that there was no significant difference in survival between these two entities in stage II CRC [ 59 ].…”

The state of applying artificial intelligence to tissue imaging for cancer research and early detection

“…Perhaps more important for clinicians is the ability to segment large regions to classify tumors and metastatic growths as well as other tissue components like tertiary lymph nodes and vascular invasion into a tissue. While cell morphology and distribution are quite important markers for pathologists, tissue segmentations would provide them with details more useful to the prognostic indicators of patient health (Huang et al, 2020). Tissue segmentation algorithms utilizing U-net, res-net, or some combination of the two have been developed to identify regions of melanoma (Thomas et al, 2021), mask and classify lymph node metastases (Khened et al, 2021), and predict angiogenic blood vessel growth into cancerous tissue (Yi et al, 2018).…”