Colonic Adenosquamous Carcinoma: A Single-Center Review of Patient Clinicopathologic Characteristics, Genetics, and Clinical Outcomes.

(1) Background: Adenosquamous carcinoma (ASC) is a rare subtype of colon cancer. Its rarity makes characterization challenging, although colonic ASC is believed to present at more advanced stages and have worse outcomes versus adenocarcinoma. This study aims to characterize the clinicopathological characteristics and clinical outcomes of colonic ASC. (2) Methods: This is a single-center, retrospective review of patients diagnosed with colonic ASC from 2000 to 2020. Data extracted included patient demographics, staging at diagnosis, tumor clinicopathologic and genetic characteristics, and clinical outcomes. (3) Results: Among 61,126 patients with colorectal cancer, 13 (0.02%) had colonic ASC, with a mean age at diagnosis of 48.7 years. The cecum/ascending colon was the most common primary site (6/13, 46.2%), and all except one patient was diagnosed with Stage III or IV disease. Among the eight patients with mismatch repair genetics available, only one was mismatch repair deficient. Eleven patients (84.6%) underwent surgery, and 11 likewise received some form of chemotherapy. Recurrence occurred in 7 of 13 patients (53.8%), and the overall five-year survival rate was 38.5%. The median survival rate was 39.4 months overall (30.5 months for Stage III, 23.7 months for Stage IV). (4) Conclusions: Overall, colonic ASC is rare, and this cohort of colonic ASC patients demonstrated advanced stage at diagnosis, frequent recurrence, and poor overall survival. Additional research remains to compare these characteristics with those of comparably staged adenocarcinoma and to develop specific management recommendations.

Oncologic Outcomes of Salvage Abdominoperineal Resection for Anal Squamous Cell Carcinoma Initially Managed with Chemoradiation.

Background: Abdominoperineal resection (APR) has been advocated for persistent or recurrent disease after failure of chemoradiation (CRT) for anal squamous cell cancer (SCC). Treatment with salvage APR can potentially achieve a cure. This study aimed to analyze oncological outcomes for salvage APR in a recent time period at a comprehensive cancer center. Methods: A retrospective review of all patients who underwent APR for biopsy-proven persistent or recurrent anal SCC between 1 January 2007 and 31 December 2020 was performed. Patients with stage IV disease at the time of initial diagnosis and patients with missing data were excluded. Univariate analysis was used with a chi-square test for categorical variables, and non-parametric tests were used for continuous variables. Kaplan-Meier survival analysis was performed to evaluate disease-specific (DSS), post-APR local recurrence-free (RFS), and disease-free survival (DFS). Results: A total of 96 patients were included in the analysis: 39 (41%) with persistent disease and 57 (59%) with recurrent SCC after chemoradiation had been completed. The median follow-up was 22 months (IQR 11-47). Forty-nine patients (51%) underwent extended APR and/or pelvic exenteration. Eight (8%) patients developed local recurrence, 30 (31%) developed local and distant recurrences, and 16 (17%) developed distant recurrences alone. The 3-year DSS, post-APR local recurrence-free survival, and disease-free survival were 53.8% (95% CI 43.5-66.5%), 54.5% (95% CI 44.4-66.8%), and 26.8% (95% CI 18.6-38.7%), respectively. In multivariate logistic regression analysis, positive microscopic margin (OR 10.0, 95% CI 2.16-46.12, p = 0.003), positive nodes in the surgical specimen (OR 9.19, 95% CI 1.99-42.52, p = 0.005), and lymphovascular invasion (OR 2.61 95% CI 1.05-6.51, p = 0.04) were associated with recurrence of disease. Gender, indication for APR (recurrent vs. persistent disease), HIV status, extent of surgery, or type of reconstruction did not influence survival outcomes. Twenty patients had targeted tumor-sequencing data available. Nine patients had PIK3CA mutations, seven of whom experienced a recurrence. Conclusions: Salvage APR for anal SCC after failed CRT was associated with poor disease-specific survival and low recurrence-free survival. Anal SCC patients undergoing salvage APR should be counseled that microscopic positive margins, positive lymph nodes, or the presence of lymphovascular invasion in the APR specimen are prognosticators for disease relapse. Our results accentuate the necessity for additional treatment strategies for the ongoing treatment challenge of persistent or recurrent anal SCC after failed CRT.

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression.

Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for immunotherapy response. However, quantification of PD-L1 status in pathology slides is challenging. Neither manual quantification nor a computer-based mimicking of manual readouts is perfectly reproducible, and the predictive performance of both approaches regarding immunotherapy response is limited. In this study, we developed a deep learning (DL) method to predict PD-L1 status directly from raw IHC image data, without explicit intermediary steps such as cell detection or pigment quantification. We trained the weakly supervised model on PD-L1-stained slides from the non-small cell lung cancer (NSCLC)-Memorial Sloan Kettering (MSK) cohort (N = 233) and validated it on the pan-cancer-Vall d'Hebron Institute of Oncology (VHIO) cohort (N = 108). We also investigated the performance of the model to predict response to immune checkpoint inhibitors (ICI) in terms of progression-free survival. In the pan-cancer-VHIO cohort, the performance was compared with tumor proportion score (TPS) and combined positive score (CPS). The DL model showed good performance in predicting PD-L1 expression (TPS ≥ 1%) in both NSCLC-MSK and pan-cancer-VHIO cohort (AUC 0.88 ± 0.06 and 0.80 ± 0.03, respectively). The predicted PD-L1 status showed an improved association with response to ICIs [HR: 1.5 (95% confidence interval: 1-2.3), P = 0.049] compared with TPS [HR: 1.4 (0.96-2.2), P = 0.082] and CPS [HR: 1.2 (0.79-1.9), P = 0.386]. Notably, our explainability analysis showed that the model does not just look at the amount of brown pigment in the IHC slides, but also considers morphologic factors such as lymphocyte conglomerates. Overall, end-to-end weakly supervised DL shows potential for improving patient stratification for cancer immunotherapy by analyzing PD-L1 IHC, holistically integrating morphology and PD-L1 staining intensity. SIGNIFICANCE: The weakly supervised DL model to predict PD-L1 status from raw IHC data, integrating tumor staining intensity and morphology, enables enhanced patient stratification in cancer immunotherapy compared with traditional pathologist assessment.