Weakly Supervised Classification for Nasopharyngeal Carcinoma with Transformer in Whole Slide Images.

Pathological examination of nasopharyngeal carcinoma (NPC) is an indispensable factor for diagnosis, guiding clinical treatment and judging prognosis. Traditional and fully supervised NPC diagnosis algorithms require manual delineation of regions of interest on the gigapixel of whole slide images (WSIs), which however is laborious and often biased. In this paper, we propose a weakly supervised framework based on Tokens-to-Token Vision Transformer (WS-T2T-ViT) for accurate NPC classification with only a slide-level label. The label of tile images is inherited from their slide-level label. Specifically, WS-T2T-ViT is composed of the multi-resolution pyramid, T2T-ViT and multi-scale attention module. The multi-resolution pyramid is designed for imitating the coarse-to-fine process of manual pathological analysis to learn features from different magnification levels. The T2T module captures the local and global features to overcome the lack of global information. The multi-scale attention module improves classification performance by weighting the contributions of different granularity levels. Extensive experiments are performed on the 802-patient NPC and CAMELYON16 dataset. WS-T2T-ViT achieves an area under the receiver operating characteristic curve (AUC) of 0.989 for NPC classification on the NPC dataset. The experiment results of CAMELYON16 dataset demonstrate the robustness and generalizability of WS-T2T-ViT in WSI-level classification.

Collagen-related gene expression level predicts the prognosis and immune therapy response.

BACKGROUND: Gastric cancer patients responded differently to the same treatment strategy and had various prognoses for the lack of biomarkers to guide the therapy choice. METHODS: RNA data of a local gastric cancer cohort with 103 patients were processed and used to explore potential treatment guiding factors. Cluster analysis was performed by non-negative matrix factorization. The expression level of collagen-related genes was evaluated by ssGSEA named collagen score (CS). Data from TCGA, ACRG, and an immune therapy cohort were utilized to explore prognosis and efficacy. Prognostic predictive power of CS was assessed using the nomogram. RESULTS: In our study, local RNA data were processed by cluster analysis, and it was found that cluster 2 contained a worse tumor infiltration status. The GSEA result showed that collagen-related pathways were differentially activated in two clusters. In TCGA and ACRG cohorts, the CS can be used as an independent prognostic factor (TCGA OS: p = 0.018, HR = 3.5; ACRG OS: p = 0.014, HR = 4.88). An immunotherapy cohort showed that the patients with higher CS had a significantly worse ORR (p = 0.0025). The high CS group contained several cell death pathways down-regulated and contained the worse tumor microenvironment. The nomogram demonstrated the survival prediction capability of collagen score. CONCLUSION: CS was verified as an independent prognostic factor and potentially reflected the therapeutic effect of immunotherapy. The CS could provide a new way to evaluate the clinical prognosis and response information helping develop the collagen-targeted treatment.

Development and validation of a collagen signature to predict the prognosis of patients with stage II/III colorectal cancer.

The tumor, nodes and metastasis (TNM) classification system provides useful but incomplete prognostic information and lacks the assessment of the tumor microenvironment (TME). Collagen, the main component of the TME extracellular matrix, plays a nonnegligible role in tumor invasion and metastasis. In this cohort study, we aimed to develop and validate a TME collagen signature (CSTME) for prognostic prediction of stage II/III colorectal cancer (CRC) and to compare the prognostic values of "TNM stage + CSTME" with that of TNM stage alone. Results indicated that the CSTME was an independent prognostic risk factor for stage II/III CRC (hazard ratio: 2.939, 95% CI: 2.180-3.962, p < 0.0001), and the integration of the TNM stage and CSTME had a better prognostic value than that of the TNM stage alone (AUC(TNM+CSTME) = 0.772, AUC TNM = 0.687, p < 0.0001). This study provided an application of "seed and soil" strategy for prognosis prediction and individualized therapy.

Using less annotation workload to establish a pathological auxiliary diagnosis system for gastric cancer.

Pathological diagnosis of gastric cancer requires pathologists to have extensive clinical experience. To help pathologists improve diagnostic accuracy and efficiency, we collected 1,514 cases of stomach H&E-stained specimens with complete diagnostic information to establish a pathological auxiliary diagnosis system based on deep learning. At the slide level, our system achieves a specificity of 0.8878 while maintaining a high sensitivity close to 1.0 on 269 biopsy specimens (147 malignancies) and 163 surgical specimens (80 malignancies). The classified accuracy of our system is 0.9034 at the slide level for 352 biopsy specimens (201 malignancies) from 50 medical centers. With the help of our system, the pathologists' average false-negative rate and average false-positive rate on 100 biopsy specimens (50 malignancies) are reduced to 1/5 and 1/2 of the original rates, respectively. At the same time, the average uncertainty rate and the average diagnosis time are reduced by approximately 22% and 20%, respectively.

Loss of Sam50 in hepatocytes induces cardiolipin-dependent mitochondrial membrane remodeling to trigger mtDNA release and liver injury.

BACKGROUND AND AIMS: Sam50, a key component of the sorting and assembly machinery (SAM) complex, is also involved in bridging mitochondrial outer-membrane and inner-membrane contacts. However, the physiological and pathological functions of Sam50 remain largely unknown. APPROACH AND RESULTS: Here we show that Sam50 interacts with MICOS (mitochondrial contact site and cristae organizing system) and ATAD3 (ATPase family AAA domain-containing protein 3) to form the Sam50-MICOS-ATAD3-mtDNA axis, which maintains mtDNA stability. Loss of Sam50 causes mitochondrial DNA (mtDNA) aggregation. Furthermore, Sam50 cooperates with Mic60 to bind to cardiolipin, maintaining the integrity of mitochondrial membranes. Sam50 depletion leads to cardiolipin externalization, which causes mitochondrial outer-membrane and inner-membrane (including crista membrane) remodeling, triggering Bax mitochondrial recruitment, mtDNA aggregation, and release. Physiologically, acetaminophen (an effective antipyretic and analgesic)-caused Sam50 reduction or Sam50 liver-specific knockout induces mtDNA release, leading to activation of the cGAS-STING pathway and liver inflammation in mice. Moreover, exogenous expression of Sam50 remarkably attenuates APAP-induced liver hepatoxicity. CONCLUSIONS: Our findings uncover the critical role of Sam50 in maintaining mitochondrial membrane integrity and mtDNA stability in hepatocytes and reveal that Sam50 depletion-induced cardiolipin externalization is a signal of mtDNA release and controls mtDNA-dependent innate immunity.

Association of Tumor-Associated Collagen Signature With Prognosis and Adjuvant Chemotherapy Benefits in Patients With Gastric Cancer.

Importance: The current TNM staging system provides limited information for prognosis prediction and adjuvant chemotherapy benefits for patients with gastric cancer (GC). Objective: To develop a tumor-associated collagen signature of GC (TACSGC) in the tumor microenvironment to predict prognosis and adjuvant chemotherapy benefits in patients with GC. Design, Setting, and Participants: This retrospective cohort study included a training cohort of 294 consecutive patients treated between January 1, 2012, and December 31, 2013, from Nanfang Hospital, Southern Medical University, People's Republic of China, and a validation cohort of 225 consecutive patients treated between October 1, 2010, and December 31, 2012, from Fujian Provincial Cancer Hospital, Fujian Medical University, People's Republic of China. In total, 146 collagen features in the tumor microenvironment were extracted with multiphoton imaging. A TACSGC was then constructed using the least absolute shrinkage and selection operator Cox proportional hazards regression model in the training cohort. Data analysis was conducted from October 1, 2020, to April 30, 2021. Main Outcomes and Measures: The association of TACSGC with disease-free survival (DFS) and overall survival (OS) was assessed. An independent external cohort was included to validate the results. Interactions between TACSGC and adjuvant chemotherapy were calculated. Results: This study included 519 patients (median age, 57 years [IQR, 49-65 years]; 360 [69.4%] male). A 9 feature-based TACSGC was built. A higher TACSGC level was significantly associated with worse DFS and OS in both the training (DFS: hazard ratio [HR], 3.57 [95% CI, 2.45-5.20]; OS: HR, 3.54 [95% CI, 2.41-5.20]) and validation (DFS: HR, 3.10 [95% CI, 2.26-4.27]; OS: HR, 3.24 [95% CI, 2.33-4.50]) cohorts (continuous variable, P < .001 for all comparisons). Multivariable analyses found that carbohydrate antigen 19-9, depth of invasion, lymph node metastasis, distant metastasis, and TACSGC were independent prognostic predictors of GC, and 2 integrated nomograms that included the 5 predictors were established for predicting DFS and OS. Compared with clinicopathological models that included only the 4 clinicopathological predictors, the integrated nomograms yielded an improved discrimination for prognosis prediction in a C index comparison (training cohort: DFS, 0.80 [95% CI, 0.73-0.88] vs 0.78 [95% CI, 0.71-0.85], P = .03; OS, 0.81 [95% CI, 0.75-0.88] vs 0.80 [95% CI, 0.73-0.86], P = .03; validation cohort: DFS, 0.78 [95% CI, 0.70-0.87] vs 0.76 [95% CI, 0.67-0.84], P = .006; OS, 0.78 [95% CI, 0.69-0.86] vs 0.75 [95% CI, 0.67-0.84], P = .002). Patients with stage II and III GC and low TACSGC levels rather than high TACSGC levels had a favorable response to adjuvant chemotherapy (DFS: HR, 0.65 [95% CI, 0.43-0.96]; P = .03; OS: HR, 0.55 [95% CI, 0.36-0.82]; P = .004; dichotomized variable, P < .001 for interaction for both comparisons). Conclusions and Relevance: The findings suggest that TACSGC provides additional prognostic information for patients with GC and may distinguish patients with stage II and III disease who are more likely to derive benefits from adjuvant chemotherapy.

Molecular profiling of Chinese systemic anaplastic large cell lymphoma patients: novel evidence of genetic heterogeneity.

BACKGROUND: Anaplastic large cell lymphoma (ALCL) is a rare non-Hodgkin lymphoma. A comprehensive understanding of the genetic and clinical heterogeneity of ALCL may help to improve the clinical management of patients with ALCL. However, due to the rarity of the disease, the genetic heterogeneity of ALCL has not been well elucidated. This study aimed to comprehensively elucidate the mutational landscape of tumor tissue samples from patients with systemic ALCL. METHODS: Thirty-six patients with systemic ALCL were enrolled in this retrospective study. Immunohistochemistry (IHC) was performed on tumor tissues at baseline to identify anaplastic lymphoma kinase (ALK) fusions. Capture-based targeted next-generation sequencing (NGS) with a panel spanning 112 lymphoma-related genes, including ALK rearrangements, was also performed on tumor tissue samples. RESULTS: A total of 102 mutations were identified in the entire cohort. Among the 36 patients included in this analysis, 14 (38.8%) were ALK positive, as determined by IHC, while NGS showed 12 patients (33.3%) to harbor ALK rearrangements. Younger patients were more likely to have ALK-positive ALCL (P=0.011). Patients with wild-type (WT) ALK were more likely to have single-nucleotide variants (SNVs) and insertions or deletions (INDELs) than patients with ALK rearrangements (P=0.027). Among the 22 patients with WT ALK, the most commonly mutated genes were TP53 (n=6, 27.3%), followed by NOTCH1 (n=5, 22.7%), KMT2D (n=3, 13.6%), KRAS (n=3, 13.6%), TET2 (n=3, 13.6%), and JAK1 (n=2, 9.1%). Mutations in PRDM1, a commonly mutated gene in ALK-negative patients, were not detected in our ALK-negative cohort. Start-loss of beta-2-microglobulin (B2M) was detected in another patient; this patient had a favorable prognosis, with an overall survival exceeding 19 months. CONCLUSIONS: Our study revealed the unique genomic profiles of Chinese ALCL patients and represents an incremental step in deepening the understanding of the genetic heterogeneity of ALCL patients.

OMA1 reprograms metabolism under hypoxia to promote colorectal cancer development.

Many cancer cells maintain enhanced aerobic glycolysis due to irreversible defective mitochondrial oxidative phosphorylation (OXPHOS). This phenomenon, known as the Warburg effect, is recently challenged because most cancer cells maintain OXPHOS. However, how cancer cells coordinate glycolysis and OXPHOS remains largely unknown. Here, we demonstrate that OMA1, a stress-activated mitochondrial protease, promotes colorectal cancer development by driving metabolic reprogramming. OMA1 knockout suppresses colorectal cancer development in AOM/DSS and xenograft mice models of colorectal cancer. OMA1-OPA1 axis is activated by hypoxia, increasing mitochondrial ROS to stabilize HIF-1α, thereby promoting glycolysis in colorectal cancer cells. On the other hand, under hypoxia, OMA1 depletion promotes accumulation of NDUFB5, NDUFB6, NDUFA4, and COX4L1, supporting that OMA1 suppresses OXPHOS in colorectal cancer. Therefore, our findings support a role for OMA1 in coordination of glycolysis and OXPHOS to promote colorectal cancer development and highlight OMA1 as a potential target for colorectal cancer therapy.