Increasing frequency of gene copy number aberrations is associated with immunosuppression and predicts poor prognosis in gastric adenocarcinoma

PTEN-mediated resistance in cancer: From foundation to future therapies

In cancer resistance, phosphatase and tensin homolog deleted (PTEN) has emerged as a prominent protagonist. PTEN exerts its influence by regulating crucial signaling pathways that govern cell proliferation, survival, and differentiation. This comprehensive review article investigates deeply into the complex realm of PTEN-mediated drug resistance mechanisms in cancers. Our journey begins by exploring PTEN's foundational role of PTEN, unveiling its significance as a molecular conductor that intricately coordinates vital cellular pathways. We thoroughly dissected the intricate milieu of PTEN alterations, including mutations, deletions, and epigenetic silencing, and elucidated their profound implications for fueling cancer growth and evading treatment. As we navigate the complex network of PTEN, we unravel the intricate interplay between PTEN and pivotal signaling pathways, such as PI3K/AKT, MAPK/ERK, and Wnt/β-catenin, further complicating the resistance landscape. This expedition, through these intricately intertwined signaling cascades, provides insight into the multifaceted mechanisms driving resistance, thereby revealing potential exploitable weaknesses. In our quest for therapeutic strategies, we need to explore innovative approaches to restore PTEN function, encompassing genetic therapies, pharmacological agents, and precision medicines tailored to PTEN status. The concept of combination therapy has emerged as a potent tool to overcome PTEN-associated resistance, offering promising synergistic interactions with standard treatments, targeted therapies, or immunotherapy. This review offers a comprehensive overview of PTEN-mediated drug resistance mechanisms in cancer and elucidates intricate interactions within this complex landscape. This underscores the central role of PTEN in drug resistance and provides valuable insights into promising strategies with the potential to reshape the future of cancer treatment.

Identifying high-risk candidates for prolonging progression-free survival in primary gastric carcinoma subject to "double invasion": an analytical approach utilizing lasso-cox regression

OBJECTIVE

To identify high-risk gastric carcinoma patients with concurrent vascular and neural invasion ("double invasion") who are at heightened risk of progression-free survival (PFS) decline, enabling personalized clinical management.

METHODS

In this multi-center retrospective study, 559 patients with double invasion who underwent curative gastrectomy between May 2002 and December 2020 were analyzed. Prognostic factors for PFS were identified using Lasso-Cox regression. Model validation included internal bootstrapping, calibration plots, and comparison against the American Joint Committee on Cancer(AJCC) 8th edition TNM staging system via Harrell's C-index, decision curve analysis (DCA), and time-dependent receiver operating characteristic (ROC) curves.

RESULTS

The nomogram integrated gender, positive lymph node count, surgical gastrectomy method, PTEN/FHIT expression levels, and maximum tumor diameter. It demonstrated superior predictive accuracy to AJCC staging, with a C-index of 0.651 (95% CI: 0.612-0.691) versus 0.543 (95% CI: 0.517-0.569). Calibration plots showed strong agreement between predicted and observed outcomes. The area under the curve(AUC) for 3- and 5-year PFS predictions were 0.719 (95% CI: 0.655-0.771) and 0.767 (95% CI: 0.670-0.841), respectively. DCA confirmed clinical utility across decision thresholds, and risk stratification effectively differentiated low- and high-risk groups. In the training cohort, the model significantly outperformed AJCC staging (NRI: 0.218, p < 0.01; IDI: 0.085, p < 0.01). However, this superiority was not statistically significant in the validation cohort (NRI: 0.141, p = 0.08; IDI: 0.031, p = 0.239).

CONCLUSION

We developed a Lasso-Cox regression-based nomogram to stratify PFS risk in gastric carcinoma patients with double invasion. While the model outperformed AJCC staging in training, validation cohort results highlight the need for further refinement. This tool holds potential for guiding tailored therapeutic strategies, though broader validation is warranted to confirm clinical applicability.

Construction of an immune-related risk score signature for gastric cancer based on multi-omics data

Early identification of gastric cancer (GC) is associated with a superior survival rate compared to advanced GC. However, the poor specificity and sensitivity of traditional biomarkers suggest the importance of identifying more effective biomarkers. This study aimed to identify novel biomarkers for the prognosis of GC and construct a risk score (RS) signature based on these biomarkers, with to validation of its predictive performance. We used multi-omics data from The Cancer Genome Atlas to analyze the significance of differences in each omics data and combined the data using Fisher's method. Hub genes were subsequently subjected to univariate Cox and LASSO regression analyses and used to construct the RS signature. The RS of each patient was calculated, and the patients were divided into two subgroups according to the RS. The RS signature was validated in two independent datasets from the Gene Expression Omnibus and subsequent analyses were subsequently conducted. Five immune-related genes strongly linked to the prognosis of GC patients were obtained, namely CGB5, SLC10A2, THPO, PDGFRB, and APOD. The results revealed significant differences in overall survival between the two subgroups (p < 0.001) and indicated the high accuracy of the RS signature. When validated in two independent datasets, the results were consistent with those in the training dataset (p = 0.003 and p = 0.001). Subsequent analyses revealed that the RS signature is independent and has broad applicability among various GC subtypes. In conclusion, we used multi-omics data to obtain five immune-related genes comprising the RS signature, which can independently and effectively predict the prognosis of GC patients with high accuracy.

Chromosomal Instability in Gastric Cancer: Role in Tumor Development, Progression, and Therapy

According to the Cancer Genome Atlas (TCGA), gastric cancers are classified into four molecular subtypes: Epstein-Barr virus-positive (EBV+), tumors with microsatellite instability (MSI), tumors with chromosomal instability (CIN), and genomically stable (GS) tumors. However, the gastric cancer (GC) with chromosomal instability remains insufficiently described and does not have effective markers for molecular and histological verification and diagnosis. The CIN subtype of GC is characterized by chromosomal instability, which is manifested by an increased frequency of aneuploidies and/or structural chromosomal rearrangements in tumor cells. Structural rearrangements in the CIN subtype of GC are not accidental and are commonly detected in chromosomal loci, being abnormal because of specific structural organization. The causes of CIN are still being discussed; however, according to recent data, aberrations in the TP53 gene may cause CIN development or worsen its phenotype. Clinically, patients with the CIN subtype of GC demonstrate poor survival, but receive the maximum benefit from adjuvant chemotherapy. In the review, we consider the molecular mechanisms and possible causes of chromosomal instability in GC, the common rearrangements of chromosomal loci and their impact on the development and clinical course of the disease, as well as the driver genes, their functions, and perspectives on their targeting in the CIN subtype of GC.