Microenvironment, systemic inflammatory response and tumor markers considering consensus molecular subtypes of colorectal cancer.

Introduction: Colorectal carcinomas (CRC) are one of the most frequent malignancies worldwide. Based on gene expression profile analysis, CRCs can be classified into four distinct subtypes also known as the consensus molecular subtypes (CMS), which predict biological behaviour. Besides CMS, several other aspects of tumor microenvironment (TME) and systemic inflammatory response (SIR) influence the outcome of CRC patients. TME and inflammation have important role in the immune (CMS1) and mesenchymal (CMS4) subtypes, however, the relationship between these and systemic inflammation has not been assessed yet. Our objective was to evaluate the connection between CMS, TME and SIR, and to analyze the correlation between these markers and routinely used tumor markers, such as CEA (Carcinoembryonic Antigen) and CA19-9 (Carbohydrate Antigen 19-9). Methods: FFPE (Formalin Fixed Paraffin Embedded) samples of 185 CRC patients were collected. TME was described using tumor-stroma ratio (TSR), Klintrup-Makinen (KM) grade, and Glasgow Microenvironment Score (GMS). CMS classification was performed on tissue microarray using MLH1, PMS2, MSH2 and MSH6, and pan-cytokeratin, CDX2, FRMD6, HTR2B and ZEB1 immunohistochemical stains. Pre-operative tumor marker levels and inflammatory markers [C-reactive protein - CRP, albumin, absolute neutrophil count (ANC), absolute lymphocyte count (ALC), absolute platelet count (APC)] and patient history were retrieved using MedSolution database. Results: Amongst TME-markers, TSR correlated most consistently with adverse clinicopathological features (p < 0.001) and overall survival (p < 0.001). Elevated CRP and modified Glasgow Prognostic Score (mGPS) were associated with worse outcome and aggressive phenotype, similarly to tumor markers CEA and CA19-9. Stroma-Tumor Marker score (STM score), a new combined score of CA19-9 and TSR delivered the second best prognostication after mGPS. Furthermore, CMS4 showed association with TSR and several laboratory markers (albumin and platelet derived factors), but not with other SIR descriptors. CMS did not show any association with CEA and CA19-9 tumor markers. Conclusion: More routinely available TME, SIR and tumor markers alone and in combination deliver reliable prognostic data for choosing the patients with higher risk for propagation. CMS4 is linked with high TSR and poor prognosis, but in overall, CMS-classification showed only limited effect on SIR- and tumor-markers.

Digital image analysis provides robust tissue microenvironment-based prognosticators in patients with stage I-IV colorectal cancer.

In patients with colorectal cancer (CRC), a promising marker is tumor-stroma ratio (TSR). Quantification issues highlight the importance of precise assessment that might be solved by artificial intelligence-based digital image analysis systems. Some alternatives have been offered so far, although these platforms are either proprietary developments or require additional programming skills. Our aim was to validate a user-friendly, commercially available software running in everyday computational environment to improve TSR assessment and also to compare the prognostic value of assessing TSR in 3 distinct regions of interests, like hotspot, invasive front, and whole tumor. Furthermore, we compared the prognostic power of TSR with the newly suggested carcinoma percentage (CP) and carcinoma-stroma percentage (CSP). Slides of 185 patients with stage I-IV CRC with clinical follow-up data were scanned and evaluated by a senior pathologist. A machine learning-based digital pathology software was trained to recognize tumoral and stromal compartments. The aforementioned parameters were evaluated in the hotspot, invasive front, and whole tumor area, both visually and by machine learning. Patients were classified based on TSR, CP, and CSP values. On multivariate analysis, TSR-hotspot was found to be an independent prognostic factor of overall survival (hazard ratio for TSR-hotspotsoftware: 2.005 [95% confidence interval (CI): 1.146-3.507], P = .011, for TSR-hotspotvisual: 1.781 [CI: 1.060-2.992], P = .029). Also, TSR was an independent predictor for distant metastasis and local relapse in most settings. Generally, software performance was comparable to visual evaluation and delivered reliable prognostication in more settings also with CP and CSP values. This study presents that software-assisted evaluation is a robust prognosticator. Our approach used a less sophisticated and thus easily accessible software without the aid of a convolutional neural network; however, it was still effective enough to deliver reliable prognostic information.

Traditional Serrated Adenoma of the Gallbladder, a Case Report.

While overwhelming majority of laparoscopic cholecystectomy specimens performed for gallstones or cholecystitis show rather typical findings, sometimes polypoid structures are also removed. These can be related to cholesterolosis or conventional adenomas, but occasionally extraordinary findings do emerge. In our case, a 67-year old lady with typical complaints of cholecystitis underwent routine laparoscopic cholecystectomy. Preoperative ultrasound revealed a polypoid mass with inflammation and without suspicion for malignancy. Microscopic examination showed partly conventional, low-grade dysplastic crypts forming a villous and rather complex structure. Ectopic crypt foci, slit-like serration pattern and serrated dysplasia with eosinophylic cytoplasm and centrally located nuclei were seen throughout the lesion, thus a traditional serrated adenoma (TSA) of the gallbladder was diagnosed. TSA represents the rarest subtype of serrated lesions in the colon and extracolonic manifestations are sporadically reported. Until now only a single case of a serrated adenoma was reported from the gallbladder. Here we describe the detailed clinical, pathological and molecular findings of our case and discuss these in the light of current literature data regarding this field.