Neoadjuvant treatment discriminates responders, but pathologic complete response is uncommon in oestrogen receptor (ER)-positive/HER2-negative early breast cancer. We aimed to assess the prognostic value of Ki-67 index after neoadjuvant endocrine therapy (NET).
We conducted a systematic literature search of PubMed, Embase, CENTRAL, and conference proceedings up to 22nd August 2023 to identify studies reporting the association of Ki-67 index after NET with recurrence-free survival (RFS) and/or overall survival (OS) in women with ER-positive/HER2-negative early breast cancer. We combined RFS and OS hazard ratios (HRs) with 95% confidence intervals (CIs).
Twelve studies including 7897 patients were analysed. Most studies were clinical trials (n = 7547) including only postmenopausal women (n = 3953) treated with aromatase inhibitor (n = 3359). Three studies evaluated Ki-67 in a preplanned core biopsy at 2-4 weeks of NET (n = 3348), while nine evaluated Ki-67 in the surgical specimen (n = 4549) after 2-24 weeks of NET. Median follow-up ranged between 37 and 95 months for RFS and 62-84 months for OS. High Ki-67 index after NET was significantly associated with worse RFS (HR 2.48, 95% CI 1.86-3.30) and OS (HR 2.66, 95% CI 1.65-4.28). A sensitivity analysis including three studies that measured Ki-67 in a preplanned core biopsy showed similar association with RFS (HR 2.41, 95% CI 1.77-3.30).
High Ki-67 after NET is associated with worse survival outcomes, even after a short course of NET, emphasising the prognostic value of this biomarker in women with ER-positive/HER2-negative early breast cancer.

Ki-67 index after neoadjuvant endocrine therapy as a prognostic biomarker in patients with ER-positive/HER2-negative early breast cancer: a systematic review and meta-analysis.

Our aim was to investigate and evaluate the influence of metformin on cancer-related biomarkers in clinical trials.
This systematic study was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Major databases, including Scopus, Web of Sciences, PubMed, Ovid-Medline, and Cochrane, were systematically reviewed by February 2020. Clinical trials investigating metformin effects on the evaluation of homeostatic models of insulin resistance (HOMA-IR), Ki-67, body mass index (BMI), fasting blood sugar (FBS), and insulin were selected for further analysis. Quality assessment was performed with version 2 of the Cochrane tool for determining the bias risk for randomized trials (RoB 2). Heterogeneity among the included studies was assessed using the Chi-square test. After quality assessment, a random effects model was performed to summarize the data related to insulin, HOMA-IR, Ki-67, and a fixed-effect model for FBS and BMI in a meta-analysis.
Nine clinical trials with 716 patients with operable breast and endometrial cancer and 331 with primary breast cancer were involved in the current systematic and meta-analysis study. Systematic findings on the nine publications indicated metformin decreased insulin levels in four studies, FBS in one, BMI in two, Ki-67 in three studies, and HOMA-IR in two study. The pooled analysis indicated that metformin had no significant effect on the following values: insulin (standardized mean differences (SMD) = -0.87, 95% confidence intervals (CI) (-1.93, 0.19), 
Patients with operable breast and endometrial cancer under metformin therapy showed no significant changes in the investigated metabolic biomarkers in the most of included study. It was also found that metformin could decrease Ki-67 in patients with operable endometrial cancer. In comparison to the results obtained of our meta-analysis, due to the high heterogeneity and bias of the included clinical trials, the present findings could not confirm or reject the efficacy of metformin for patients with breast cancer and endometrial cancer.

Impact of Metformin on Cancer Biomarkers in Non-Diabetic Cancer Patients: A Systematic Review and Meta-Analysis of Clinical Trials.

The objective of the study was to compare the expression of immunohistochemical (IHC) markers of oral submucous fibrosis (OSMF) (non-transformed group) to those of oral squamous cell carcinoma (OSCC) transformed from OSMF (transformed group). The search for comparative cross-sectional studies was carried out in PubMed and Scopus abiding to the PICO criteria, where expression of IHC markers in OSMF were compared with that of OSCC transformed from OSMF. The cellular distribution, number of positive cases, staining intensity, and mean immunoreactive score (IRS) of each IHC marker were evaluated in both groups. A total of 14 studies were included in the systematic review, in which immunoexpression of 15 epithelial and 4 connective tissue biomarkers were evaluated. Expression of β1-integrin, OCT-3, CD1a, CD207, survivin, Dickkopf-1, COX-2, hTERT, CTGF, MDM2, Ki-67, and α-SMA were increased during transformation of OSMF to OSCC. Conversely, expression of PTEN and lysyl oxidase decreased during transformation of OSMF to OSCC. Expression of a group of epithelial markers, such as COX2, hTERT, CTGF, survivin, MDM2, and p53, was 38 times lower in the non-transformed group cases compared to transformed group cases (95% CI: 58% to 10%; 

Comparison of Immunohistochemical Markers in Oral Submucous Fibrosis and Oral Submucous Fibrosis Transformed to Oral Squamous Cell Carcinoma-A Systematic Review and Meta-Analysis.

Deep learning for cephalometric landmark detection: systematic review and meta-analysis. Schwendicke F, Chaurasia A, Arsiwala L, Lee JH, Elhennawy K, Jost-Brinkmann PG, Demarco F, Krois J. Clin Oral Investig. 2021 Jul;25(7):4299-4309.
This study was self-funded by the authors and their institutions.
Systematic review and meta-analysis.

DEEP LEARNING ALGORITHMS HAVE HIGH ACCURACY FOR AUTOMATED LANDMARK DETECTION ON 2D LATERAL CEPHALOGRAMS.

Is there a shared genetic or causal association of endometriosis with asthma or what biological mechanisms may underlie their potential relationships?
Our results confirm a significant but non-causal association of endometriosis with asthma implicating shared genetic susceptibility and biological pathways in the mechanisms of the disorders, and potentially, their co-occurrence.
Some observational studies have reported a pattern of co-occurring relationship between endometriosis and asthma; however, there is conflicting evidence and the aetiology, as well as the underlying mechanisms of the relationship, remain unclear.
We applied multiple statistical genetic approaches in the analysis of well-powered, genome-wide association study (GWAS) summary data to comprehensively assess the relationship of endometriosis with asthma. Endometriosis GWAS from the International Endogene Consortium (IEC, 17 054 cases and 191 858 controls) and asthma GWAS from the United Kingdom Biobank (UKB, 26 332 cases and 375 505 controls) were analysed. Additional asthma data from the Trans-National Asthma Genetic Consortium (TAGC, 19 954 cases and 107 715 controls) were utilized for replication testing.
We assessed single-nucleotide polymorphism (SNP)-level genetic overlap and correlation between endometriosis and asthma using SNP effect concordance analysis (SECA) and linkage disequilibrium score regression analysis (LDSC) methods, respectively. GWAS meta-analysis, colocalization (GWAS-PW), gene-based and pathway-based functional enrichment analysis methods were applied, respectively, to identify SNP loci, genomic regions, genes and biological pathways shared by endometriosis and asthma. Potential causal associations between endometriosis and asthma were assessed using Mendelian randomization (MR) methods.
SECA revealed significant concordance of SNP risk effects across the IEC endometriosis and the UKB asthma GWAS. Also, LDSC analysis found a positive and significant genetic correlation (rG = 0.16, P = 2.01 × 10-6) between the two traits. GWAS meta-analysis of the IEC endometriosis and UKB asthma GWAS identified 14 genome-wide significant (Pmeta-analysis < 5.0 × 10-8) independent loci, five of which are putatively novel. Three of these loci were consistently replicated using TAGC asthma GWAS and reinforced in colocalization and gene-based analyses. Additional shared genomic regions were identified in the colocalization analysis. MR found no evidence of a significant causal association between endometriosis and asthma. However, combining gene-based association results across the GWAS for endometriosis and asthma, we identified 17 shared genes with a genome-wide significant Fisher's combined P-value (FCPgene) <2.73 × 10-6. Additional analyses (independent gene-based analysis) replicated evidence of gene-level genetic overlap between endometriosis and asthma. Biological mechanisms including 'thyroid hormone signalling', 'abnormality of immune system physiology', 'androgen biosynthetic process' and 'brain-derived neurotrophic factor signalling pathway', among others, were significantly enriched for endometriosis and asthma in a pathway-based analysis.
The GWAS for endometriosis data were sourced from the International Endogen Consortium (IEC) and can be accessed by contacting the consortium. The GWAS data for asthma are freely available online at Lee Lab (https://www.leelabsg.org/resources) and from the Trans-National Asthma Genetic Consortium (TAGC).
Given we analysed GWAS datasets from mainly European populations, our results may not be generalizable to other ancestries.
This study provides novel insights into mechanisms underpinning endometriosis and asthma, and potentially their observed relationship. Findings support a co-occurring relationship of endometriosis with asthma largely due to shared genetic components. Agents targeting 'selective androgen receptor modulators' may be therapeutically relevant in both disorders. Moreover, SNPs, loci, genes and biological pathways identified in our study provide potential targets for further investigation in endometriosis and asthma.
National Health and Medical Research Council (NHMRC) of Australia (241,944, 339,462, 389,927, 389,875, 389,891, 389,892, 389,938, 443,036, 442,915, 442,981, 496,610, 496,739, 552,485, 552,498, 1,026,033 and 1,050,208), Wellcome Trust (awards 076113 and 085475) and the Lundbeck Foundation (R102-A9118 and R155-2014-1724). All researchers had full independence from the funders. Authors do not have any conflict of interest.

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