Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Purpose: Varlitinib is a pan-human epidermal growth factor receptor (HER) inhibitor targeting epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), and HER4. We present a phase Ib/II study of a combination of varlitinib and weekly paclitaxel as a second-line treatment for patients with EGFR/HER2 co-expressing advanced gastric cancer (AGC). Materials and Methods: Patients whose tumors with EGFR and HER2 overexpression by immunohistochemistry (≥ 1+) were enrolled. Varlitinib and paclitaxel were investigated every 4 weeks. After determining the recommended phase II dose (RP2D) in phase Ib, a phase II study was conducted to evaluate the antitumor activity. Results: RP2D was treated with a combination of varlitinib (300 mg twice daily) and paclitaxel. Among 27 patients treated with RP2D, the median progression-free survival and overall survival (OS) were 3.3 months (95% confidence interval [CI], 1.7 to 4.9) and 7.9 months (95% CI, 5.0 to 10.8), respectively, with a median follow-up of 15.7 months. Among 16 patients with measurable disease, the objective response rate (ORR) and disease control rate were 31% and 88%, respectively. Patients with strong HER2 expression (n=8) had a higher ORR and longer OS, whereas those with strong EGFR expression (n=3) had poorer outcomes. The most common adverse events (AEs) of any grade were neutropenia (52%), diarrhea (27%), aspartate aminotransferase/alanine transaminase elevation (22%), and nausea (19%). No treatment-related deaths or unexpected AEs resulting from treatment cessation were observed in patients with RP2D. Conclusion A combination of varlitinib and paclitaxel displayed manageable toxicity and modest antitumor activity in patients with EGFR/HER2 co-expressing AGC who progressed after first-line chemotherapy.

This study was conducted to investigate potential differences in vaccine efficacy between patients undergoing palliative chemotherapy and receiving adjuvant chemotherapy. Additionally, the study proved the influence of vaccination timing on vaccine efficacy during active chemotherapy. Anti-receptor-binding domain (RBD) IgG binding antibody assays and surrogate neutralizing antibody assays were performed after BNT162b2 or mRNA-1273 vaccination in 45 solid cancer patients (23 adjuvant and 22 palliative chemotherapy) and in 24 healthy controls before vaccination (baseline), at every two to four weeks after the first (post-dose 1) and the second vaccination (post-dose 2). The levels of anti-RBD IgG and neutralizing antibodies increased significantly from baseline through post-dose 1 to post-dose 2 in all three groups. At the post-dose 1, the anti-RBD IgG and neutralizing antibody levels were significantly lower in cancer patients than in healthy controls. However, by post-dose 2, the seropositivity of anti-RBD IgG and neutralizing antibodies uniformly reached 100% across all groups, with no significant disparity in antibody levels among the three groups. Moreover, the antibody titers were not significantly different between patients with a vaccine and chemotherapy interval of more than 14 days or those with less than 14 days. This study demonstrated that after second doses of mRNA COVID-19 vaccines, humoral immune responses in patients receiving chemotherapy were comparable to those of healthy controls, regardless of whether the purpose of the anti-cancer treatment was palliative or adjuvant. Furthermore, the timing of vaccination did not affect the level of humoral immunity after the second vaccination.

Background: Inter-hospital transfers of severely injured patients are inevitable due to limited resources. We investigated the association between inter-hospital transfer and the prognosis of pediatric injury using the Korean multi-institutional injury registry. Methods: This retrospective observational study was conducted from January 2013 to December 2017; data for hospitalized subjects aged < 18 years were extracted from the Emergency Department-based Injury in Depth Surveillance database, in which 22 hospitals are participating as of 2022. The survival rates of the direct transfer group and the interhospital transfer group were compared, and risk factors affecting 30-day mortality and 72-hour mortality were analyzed. Results: The total number of study subjects was 18,518, and the transfer rate between hospitals was 14.5%. The overall mortality rate was 2.3% (n = 422), the 72-hour mortality was 1.7% (n = 315) and the 30-day mortality rate was 2.2% (n = 407). The Kaplan-Meier survival curve revealed a lower survival rate in the inter-hospital transfer group than in the direct visit group (log-rank, P < 0.001). Cox proportional hazards regression analysis showed that interhospital transfer group had a higher 30-day mortality rate and 72-hour mortality (hazard ratio [HR], 1.681; 95% confidence interval [CI], 1.232–2.294 and HR, 1.951; 95% CI, 1.299–2.930) than direct visit group when adjusting for age, sex, injury severity, and head injury. Conclusion Among the pediatric injured patients requiring hospitalization, inter-hospital transfer in the emergency department was associated with the 30-day mortality rate and 72-hour mortality rate in Korea.

Background: Tumor spread through air spaces (STAS) is a recently discovered risk factor for lung adenocarcinoma (LUAD). The aim of this study was to investigate specific genetic alterations and anticancer immune responses related to STAS. By using a machine learning algorithm and drug screening in lung cancer cell lines, we analyzed the effect of Janus kinase 2 (JAK2) on the survival of patients with LUAD and possible drug candidates. Methods: This study included 566 patients with LUAD corresponding to clinicopathological and genetic data. For analyses of LUAD, we applied gene set enrichment analysis (GSEA), in silico cytometry, pathway network analysis, in vitro drug screening, and gradient boosting machine (GBM) analysis. Results: The patients with STAS had a shorter survival time than those without STAS (P < 0.001). We detected gene set-related downregulation of JAK2 associated with STAS using GSEA. Low JAK2 expression was related to poor prognosis and a low CD8+ T-cell fraction. In GBM, JAK2 showed improved survival prediction performance when it was added to other parameters (T stage, N stage, lymphovascular invasion, pleural invasion, tumor size). In drug screening, mirin, CCT007093, dihydroretenone, and ABT737 suppressed the growth of lung cancer cell lines with low JAK2 expression. Conclusion In LUAD, low JAK2 expression linked to the presence of STAS might serve as an unfavorable prognostic factor. A relationship between JAK2 and CD8+ T cells suggests that STAS is indirectly related to the anticancer immune response. These results may contribute to the design of future experimental research and drug development programs for LUAD with STAS.