Shanghai Yunying Medical Technology Co., Ltd.

Immunotherapy benefits gastrointestinal tumor patients. But traditional biomarkers like TMB and MSI can’t precisely identify beneficiaries. Phosphatidylinositol - 3,4,5 - triphosphate - dependent Rac exchange factor 2 (PREX2) plays a complex role in tumorigenesis.

In a retrospective study of 1764 patients (1385 colorectal, 379 gastric), NGS of 639 genes and PD - L1 staining were done.

In colorectal cancer, PREX2 mutations were associated with increased TMB, MSI, TMB-H, and MSI-H. Mechanistically, this is related to an increased number of tumor pathway mutations, higher PD - L1 expression, increased immune infiltration, and immune - related pathway enrichment. Cetuximab and Bortezomib sensitivity was higher in PREX2 - mutated colorectal cancer. In gastric cancer, there are no established immune associations with PREX2 mutations.

PREX2 mutations may serve as a novel predictive biomarker for immunotherapy in CRC, potentially enhancing antitumor immunity via microenvironment modulation, but lack predictive value in GC. These findings highlight PREX2's role in refining patient stratification for immune checkpoint inhibitors.

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (MTB), has similar clinical, radiological, and histopathological characteristics to sarcoidosis (SA). Accurately distinguishing SA from TB remains a clinical challenge.

A total of 44 TB patients and 47 SA patients who were clinically diagnosed using chest radiography, pathological examination, routine smear microscopy, and microbial culture were enrolled in this study. The MTB genome was captured and sequenced directly from tissue specimens obtained upon operation or biopsy, and the feasibility of next-generation sequencing (NGS) for the MTB genome in the differential diagnosis of TB from SA was evaluated.

Using a depth >10× and coverage >15% of the sequencing data, TB patients were identified via the NGS approach directly using operation or biopsy specimens without clinical pretreatment. The sensitivity, specificity, and concordance of the NGS method were 81.8% (36/44), 95.7% (45/47), and 89.0% (81/91), respectively (kappa = 0.78, 95% confidence interval 0.65-0.91; P<0.001).

This study established an improved NGS strategy for rapidly distinguishing patients with TB from those with SA and has potential clinical benefits.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Several studies have indicated that rectal cancer is significantly different from colon cancer in terms of treatment, prognosis, and metastasis. Recently, the differential mRNA expression of colon cancer and rectal cancer has received a great deal of attention. The current study aimed to identify significant differences between colon cancer and rectal cancer based on RNA sequencing (RNA-seq) data via support vector machines (SVM). Here, 393 CRC samples from the The Cancer Genome Atlas (TCGA) database were investigated, including 298 patients with colon cancer and 95 with rectal cancer. Following the random forest (RF) analysis of the mRNA expression data, 96 genes such as HOXB13, PRAC, and BCLAF1 were identified and utilized to build the SVM classification model with the Leave-One-Out Cross-validation (LOOCV) algorithm. In the training (n=196) and the validation cohorts (n=197), the accuracy (82.1 % and 82.2 %, respectively) and the AUC (0.87 and 0.91, respectively) indicated that the established optimal SVM classification model distinguished colon cancer from rectal cancer reasonably. However, additional experiments are required to validate the predicted gene expression levels and functions.