Yang Cao

Integrative analysis from multi‐center studies identifies a weighted gene co‐expression network analysis‐based Tregs signature in ovarian cancer

AbstractOvarian cancer (OC) is a malignancy associated with poor prognosis and has been linked to regulatory T cells (Tregs) in the immune microenvironment. Nevertheless, the association between Tregs‐related genes (TRGs) and OC prognosis remains incompletely understood. The xCell algorithm was used to analyze Tregs scores across multiple cohorts. Weighted gene co‐expression network analysis (WGCNA) was utilized to identify potential TRGs and molecular subtypes. Furthermore, we used nine machine learning algorithms to create risk models with prognostic indicators for patients. Reverse transcription‐quantitative polymerase chain reaction and immunofluorescence staining were used to demonstrate the immunosuppressive ability of Tregs and the expression of key TRGs in clinical samples. Our study found that higher Tregs scores were significantly correlated with poorer overall survival. Recurrent patients exhibited increased Tregs infiltration and reduced CD8+ T cell. Moreover, molecular subtyping using seven key TRGs revealed that subtype B exhibited higher enrichment of multiple oncogenic pathways and had a worse prognosis. Notably, subtype B exhibited high Tregs levels, suggesting immune suppression. In addition, we validated machine learning‐derived prognostic models across multiple platform cohorts to better distinguish patient survival and predict immunotherapy efficacy. Finally, the differential expression of key TRGs was validated using clinical samples. Our study provides novel insights into the role of Tregs in the immune microenvironment of OC. We identified potential therapeutic targets derived from Tregs (CD24, FHL2, GPM6A, HOXD8, NAP1L5, REN, and TOX3) for personalized treatment and created a machining learning‐based prognostic model for OC patients, which could be useful in clinical practice.

REG3A promotes proliferation and DDP resistance of ovarian cancer cells by activating the PI3K/Akt signaling pathway

AbstractThis study explored the effect of Regenerating Islet‐Derived 3‐Alpha (REG3A) on ovarian cancer (OC) progression. REG3A expression was scrutinized in clinical tissues of 97 OC cases by quantitative real‐time polymerase chain reaction (qRT‐PCR). REG3A expression in OC cells and cisplatin (DDP) resistance OC cells was regulated by transfection. LY294002 (10 μM, inhibitor of the PI3K/Akt signaling pathway) was used to treat OC cells and DDP resistance OC cells. Cell counting kit‐8 and methyl‐thiazolyl‐tetrazolium assays were applied for proliferation and DDP resistance detection. Flow cytometry was utilized for cell cycle and apoptosis analysis. The effect of REG3A on the OC cell in vivo growth was researched by establishing xenograft tumor model via using nude mice using nude mice. The expression of genes in clinical samples, cells and xenograft tumor tissues was investigated by qRT‐PCR, Western blot and immunohistochemistry. As a result, REG3A was over‐expressed in OC patients and cells, associating with dismal prognosis of patients. REG3A knockdown repressed proliferation, DDP resistance, induced cell cycle arrest and apoptosis of OC cells, and reduced the expression MDR‐1, Cyclin D1, Cleaved caspase 3 proteins and the PI3K/Akt signaling pathway activity in OC cells. LY294002 treatment abrogated the promotion effect of REG3A on OC cell proliferation, apoptosis inhibition and DDP resistance. REG3A knockdown suppressed the in vivo growth of OC cells. Thus, REG3A promoted proliferation and DDP resistance of OC cells by activating the PI3K/Akt signaling pathway. REG3A might be a promising target for the clinical treatment of OC.

Risk of Injuries around Diagnosis of Cervical Cancer and Its Precursor Lesions: A Nationwide Cohort Study in Sweden

Abstract Background: Highly increased risk of injuries has been noted around the time of cancer diagnosis. Whether there is a similar increase in risk around the diagnosis of cervical cancer and its precursor lesions was unknown. Methods: We performed a cohort study including 3,016,307 Swedish women that participated in cervical screening during 2001 to 2012. We calculated the incidence rates (IR) of hospitalized iatrogenic or noniatrogenic injuries during the diagnostic workup, and the time interval from smear or punch biopsy until surgical treatment or 2 months after the last smear or biopsy, among women with invasive cervical cancer (ICC) or its precursor lesions. We calculated the IRs of injuries during the 2 months after a normal smear among the other women as reference. IR ratios (IRR) and 95% confidence intervals (CI) were calculated using Poisson regression. Results: Compared with other women, there was an increased rate of iatrogenic injuries during the diagnostic workup of women with ICC (IR, 0.58 per 1,000 person-months; IRR, 8.55; 95% CI, 3.69–19.80) as well as of women with cervical intraepithelial neoplasia grade 3 and adenocarcinoma in situ (IR, 0.09 per 1,000 person-months; IRR, 3.04; 95% CI, 1.73–5.34). We also found an increased rate of noniatrogenic injuries during the diagnostic workup of women with invasive cancer (IR, 0.65 per 1,000 person-months; IRR, 2.48; 95% CI, 1.30–4.47). Conclusions: Although rare, there was an increased risk of inpatient care for iatrogenic and noniatrogenic injuries during the diagnostic workup of women with ICC. Impact: Women experienced burden of medical complications and psychologic distress around diagnosis of a potential cervical cancer.