Background: Tumor-infiltrating lymphocytes (TILs) are clinically significant in triple-negative breast cancer (TNBC). Although a standardized methodology for visual TILs assessment (VTA) exists, it has several inherent limitations. We established a deep learning-based computational TIL assessment (CTA) method broadly following VTA guideline and compared it with VTA for TNBC to determine the prognostic value of the CTA and a reasonable CTA workflow for clinical practice. Methods: We trained three deep neural networks for nuclei segmentation, nuclei classification and necrosis classification to establish a CTA workflow. The automatic TIL (aTIL) score generated was compared with manual TIL (mTIL) scores provided by three pathologists in an Asian (n = 184) and a Caucasian (n = 117) TNBC cohort to evaluate scoring concordance and prognostic value. Findings: The intraclass correlations (ICCs) between aTILs and mTILs varied from 0.40 to 0.70 in two cohorts. Multivariate Cox proportional hazards analysis revealed that the aTIL score was associated with disease free survival (DFS) in both cohorts, as either a continuous [hazard ratio (HR)=0.96, 95% CI 0.94À0.99] or dichotomous variable (HR=0.29, 95% CI 0.12À0.72). A higher C-index was observed in a composite mTIL/aTIL threetier stratification model than in the dichotomous model, using either mTILs or aTILs alone. Interpretation: The current study provides a useful tool for stromal TIL assessment and prognosis evaluation for patients with TNBC. A workflow integrating both VTA and CTA may aid pathologists in performing risk management and decision-making tasks.

The "macrotrabecular-massive" (MTM) pattern of hepatocellular carcinoma (HCC) has been suggested to represent a distinct HCC subtype and is associated with specific molecular features. Since the immune microenvironment is heterogenous in HCC, it is important to evaluate the immune microenvironment of this novel variant. CMTM6, a key regulator of PD-L1, is an important immunocheckpoint inhibitor. This study aimed to evaluate the prognostic effect of CMTM6/PD-L1 coexpression and its relationship with inflammatory cells in HCC. We analyzed 619 HCC patients and tumors were classified into MTM and non-MTM HCC subtypes. The expression levels of CMTM6 and PD-L1 in tumor and inflammatory cells were evaluated by immunohistochemistry. The density of inflammatory cells in the cancer cell nest was calculated. Tumoral PD-L1 expression and inflammatory cell density were higher in the MTM type than in the non-MTM type. CMTM6-high expression was significantly associated with shorter OS and DFS than CMTM6-low expression in the whole HCC patient population and the MTM HCC patient population. Moreover, MTM HCC patients with CMTM6/PD-L1 coexpression experienced a higher risk of HCC progression and death. In addition, CMTM6/PD-L1 coexpression was shown to be related to a high density of inflammatory cells. Notably, a new immune classification, based on CMTM6/PD-L1 coexpression and inflammatory cells, successfully stratified OS and DFS in MTM HCC. CMTM6/PD-L1 coexpression has an adverse effect on the prognosis of HCC patients, especially MTM HCC patients. Our study provides evidence for the combination of immune status assessment with anti-CMTM6 and anti-PD-L1 therapy in MTM HCC patients.

No abstract

Background: We retrospectively compared the prognostic value between the AJCC 8th edition anatomic (AS) and prognostic staging (PS) system for triple negative breast cancer (TNBC) in a cohort from two involved institutions and a large population database. Methods: Clinicopathological data of TNBCs were identified in two involved institutions (SYSUCC-PWH cohort). Data from SEER database during 2010-2015 was also accessed. We restaged all cases into AS and PS group according to the AJCC 8th staging system. Results: A total of 611 and 31,941 TNBCs were identified in two cohorts, with a median follow-up of 53.5 and 27 months respectively. PS upstaged 46.1% of patients in SYSUCC-PWH cohort, and 62.4% in SEER cohort. No significant difference was observed in C index between AS and PS models for disease-specific survival (DSS), progression-free survival (PFS) or overall survival (OS) in either cohort. χ2 statistic and Hazard Ratio for PFS, DSS and OS showed better discrimination between IA and IB, IIB and IIIA, IIIA and IIIB in AS model than PS model. Besides, patients with IIIC unchanged stage showed worse PFS compared to those with AS IIIA or IIIB upstaged to PS IIIC in both cohorts(p = 0.049, p < 0.001). Conclusions: Our findings demonstrated that prognostic staging system did not provide better discriminatory ability in predicting TNBCs prognosis than anatomic staging system.

Background: Metaplastic breast carcinoma (MBC) is a rare histological type of breast cancer, which commonly shows resistance to standard therapies and is associated with poor prognosis. The immune microenvironment in MBC and its significance has not been well established due to its low incurrence rate and complex components. We aimed to investigate the diversity of immune parameters including subsets of TILs and PDL1/PD1 expression in MBC, as well as its correlation with prognosis. Methods: A total of 60 patients diagnosed with MBC from January 2006 to December 2017 were included in our study. The percentage (%) and quantification (per mm 2) of TILs and presence of tertiary lymphoid structures (TLS) were evaluated by hematoxylin and eosin staining (HE). The quantification of CD4+, CD8+ TILs (per mm 2), and PD-1/PDL1 expression were evaluated through immunohistochemistry and analyzed in relation to clinicopathological characteristics. A ≥ 1% membranous or cytoplasmatic expression of PD1 and PDL1 was considered a positive expression. Results: We found squamous cell carcinoma MBC (33/60, 55%) exhibiting most TILs of all the MBC subtypes (p = 0.043). Thirty-three of 60 (50%) of the patients had coexisting invasive ductal carcinoma of no special type (IDC-NST), and the average percentage of TILs in MBC components was lower compared with NST components (p < 0.001). Thirty (50%) patients exhibited positive (≥ 1%) PDL1 expression in their tumor cells, while 36 (60%) had positive (≥ 1%) PDL1 expression in their TILs. Twenty-seven (45%) of all the patients had positive (≥ 1%) PD1 expression in their tumor cells and 33 (55%) had PD1-positive (≥ 1%) stromal TILs. More CD8+ TILs were associated with positive PDL1 expression of tumor cells as well as positive PD1 expression in stromal cells. Greater number of stromal TILS (> 300/mm 2 , 20%), CD4+ TILs (> 250/mm 2), and CD8+ TILs (> 70/mm 2) in MBC were found associated with longer disease-free survival. Positive expression of PDL1 in tumor cells (≥ 1%) and PD1 in stromal cells (≥ 1%) were also associated with longer survival. Conclusions: The immune characteristics differ in various subtypes as well as components of MBC. Immune parameters are key predictive factors of MBC and provide the clinical significance of applying immune checkpoint therapies in patients with MBC.