Akihiko Ueda

Artificial Intelligence-Based Histopathological Subtyping of High-Grade Serous Ovarian Cancer

Four subtypes of ovarian high-grade serous carcinoma (HGSC) have previously been identified, each with different prognoses and drug sensitivities. However, the accuracy of classification depended on the assessor's experience. This study aimed to develop a universal algorithm for HGSC-subtype classification using deep learning techniques. An artificial intelligence (AI)-based classification algorithm, which replicates the consensus diagnosis of pathologists, was formulated to analyze the morphological patterns and tumor-infiltrating lymphocyte counts for each tile extracted from whole slide images of ovarian HGSC available in The Cancer Genome Atlas (TCGA) data set. The accuracy of the algorithm was determined using the validation set from the Japanese Gynecologic Oncology Group 3022A1 (JGOG3022A1) and Kindai and Kyoto University (Kindai/Kyoto) cohorts. The algorithm classified the four HGSC-subtypes with mean accuracies of 0.933, 0.910, and 0.862 for the TCGA, JGOG3022A1, and Kindai/Kyoto cohorts, respectively. To compare mesenchymal transition (MT) with non-MT groups, overall survival analysis was performed in the TCGA data set. The AI-based prediction of HGSC-subtype classification in TCGA cases showed that the MT group had a worse prognosis than the non-MT group (P = 0.017). Furthermore, Cox proportional hazard regression analysis identified AI-based MT subtype classification prediction as a contributing factor along with residual disease after surgery, stage, and age. In conclusion, a robust AI-based HGSC-subtype classification algorithm was established using virtual slides of ovarian HGSC.

A Deep Learning–Based Assessment Pipeline for Intraepithelial and Stromal Tumor-Infiltrating Lymphocytes in High-Grade Serous Ovarian Carcinoma

Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with epithelial ovarian cancer. However, TIL evaluation has not been used in routine clinical practice because of reproducibility issues. The current study developed two convolutional neural network models to detect TILs and to determine their spatial location in whole slide images, and established a spatial assessment pipeline to objectively quantify intraepithelial and stromal TILs in patients with high-grade serous ovarian carcinoma. The predictions of the established models showed a significant positive correlation with the number of CD8

Incidence of gastrointestinal perforation associated with bevacizumab in combination with neoadjuvant chemotherapy as first-line treatment of advanced ovarian, fallopian tube, or peritoneal cancer: analysis of a Japanese healthcare claims database

To assess the incidence of bevacizumab-associated gastrointestinal (GI) perforation during first-line treatment of patients with ovarian, fallopian tube, or peritoneal cancer receiving neoadjuvant chemotherapy (NAC) in Japanese real-world clinical practice. A retrospective study was conducted using a healthcare claims database owned by Medical Data Vision Co., Ltd. (study period, 2008-2020). Patients who initiated first-line treatment of ovarian, fallopian tube, or peritoneal cancer were identified and divided into NAC and primary debulking surgery (PDS) groups. The incidence of bevacizumab-associated GI perforation was compared within the NAC group and between the groups. Paclitaxel + carboplatin (TC) was most commonly used as first-line treatment (39.5% and 59.6% in the NAC and PDS groups, respectively). TC + bevacizumab was used in 9.3% and 11.6% of patients in the NAC and PDS groups, respectively. In the NAC group receiving TC, the proportion of patients with risk factors for GI perforation was lower among patients with versus without concomitant bevacizumab. The incidence of GI perforation in the NAC group was 0.38% (1/266 patients) in patients receiving TC + bevacizumab and 0.18% (2/1,131 patients) in patients receiving TC without bevacizumab (risk ratio=2.13; 95% confidence interval [CI]=0.19 to 23.36; risk difference=0.20; 95% CI=-0.58 to 0.97). None of the 319 patients in the PDS group receiving TC + bevacizumab had GI perforation. No notable increase was observed in GI perforation associated with NAC containing bevacizumab. We conclude that bevacizumab is prescribed with sufficient care in Japan to avoid GI perforation.

CXCL13-producing CD4+ T cells accumulate in the early phase of tertiary lymphoid structures in ovarian cancer

Tertiary lymphoid structures (TLS) are transient ectopic lymphoid aggregates whose formation might be caused by chronic inflammation states, such as cancer. However, how TLS are induced in the tumor microenvironment (TME) and how they affect patient survival are not well understood. We investigated TLS distribution in relation to tumor infiltrating lymphocytes (TILs) and related gene expression in high-grade serous ovarian cancer (HGSC) specimens. CXCL13 gene expression correlated with TLS presence and the infiltration of T cells and B cells, and it was a favorable prognostic factor for patients with HGSC. Coexistence of CD8+ T cells and B cell lineages in the TME significantly improved the prognosis of HGSC and was correlated with the presence of TLS. CXCL13 expression was predominantly coincident with CD4+ T cells in TLS and CD8+ T cells in TILs, and it shifted from CD4+ T cells to CD21+ follicular DCs as TLS matured. In a mouse ovarian cancer model, recombinant CXCL13 induced TLS and enhanced survival by the infiltration of CD8+ T cells. These results suggest that TLS formation was associated with CXCL13-producing CD4+ T cells and that TLS facilitated the coordinated antitumor response of cellular and humoral immunity in ovarian cancer.

Human papillomavirus vaccine effectiveness by age at first vaccination among Japanese women

AbstractIn Japan, the National Immunization Program against human papillomavirus (HPV) targets girls aged 12‐16 years, and catch‐up vaccination is recommended for young women up to age 26 years. Because HPV infection rates increase soon after sexual debut, we evaluated HPV vaccine effectiveness by age at first vaccination. Along with vaccination history, HPV genotyping results from 5795 women younger than 40 years diagnosed with cervical intraepithelial neoplasia grade 2‐3 (CIN2‐3), adenocarcinoma in situ (AIS), or invasive cervical cancer were analyzed. The attribution of vaccine‐targeted types HPV16 or HPV18 to CIN2‐3/AIS was 47.0% for unvaccinated women (n = 4297), but 0.0%, 13.0%, 35.7%, and 39.6% for women vaccinated at ages 12‐15 years (n = 36), 16‐18 years (n = 23), 19–22 years (n = 14), and older than 22 years (n = 91), respectively, indicating the greater effectiveness of HPV vaccination among those initiating vaccination at age 18 years or younger (P < .001). This finding was supported by age at first sexual intercourse; among women with CIN2‐3/AIS, only 9.2% were sexually active by age 14 years, but the percentage quickly increased to 47.2% by age 16 and 77.1% by age 18. Additionally, the HPV16/18 prevalence in CIN2‐3/AIS was 0.0%, 12.5%, and 40.0% for women vaccinated before (n = 16), within 3 years (n = 8), and more than 3 years after (n = 15) first intercourse, respectively (P = .004). In conclusion, our data appear to support routine HPV vaccination for girls aged 12‐14 years and catch‐up vaccination for adolescents aged 18 years and younger in Japan.