Autophagy gene haploinsufficiency drives chromosome instability, increases migration, and promotes early ovarian tumors.

Autophagy, particularly with BECN1, has paradoxically been highlighted as tumor promoting in Ras-driven cancers, but potentially tumor suppressing in breast and ovarian cancers. However, studying the specific role of BECN1 at the genetic level is complicated due to its genomic proximity to BRCA1 on both human (chromosome 17) and murine (chromosome 11) genomes. In human breast and ovarian cancers, the monoallelic deletion of these genes is often co-occurring. To investigate the potential tumor suppressor roles of two of the most commonly deleted autophagy genes in ovarian cancer, BECN1 and MAP1LC3B were knocked-down in atypical (BECN1+/+ and MAP1LC3B+/+) ovarian cancer cells. Ultra-performance liquid chromatography mass-spectrometry metabolomics revealed reduced levels of acetyl-CoA which corresponded with elevated levels of glycerophospholipids and sphingolipids. Migration rates of ovarian cancer cells were increased upon autophagy gene knockdown. Genomic instability was increased, resulting in copy-number alteration patterns which mimicked high grade serous ovarian cancer. We further investigated the causal role of Becn1 haploinsufficiency for oncogenesis in a MISIIR SV40 large T antigen driven spontaneous ovarian cancer mouse model. Tumors were evident earlier among the Becn1+/- mice, and this correlated with an increase in copy-number alterations per chromosome in the Becn1+/- tumors. The results support monoallelic loss of BECN1 as permissive for tumor initiation and potentiating for genomic instability in ovarian cancer.

FairSubset: A tool to choose representative subsets of data for use with replicates or groups of different sample sizes.

High-impact journals are promoting transparency of data. Modern scientific methods can be automated and produce disparate samples sizes. In many cases, it is desirable to retain identical or pre-defined sample sizes between replicates or groups. However, choosing which subset of originally acquired data that best matches the entirety of the data set without introducing bias is not trivial. Here, we released a free online tool, FairSubset, and its constituent Shiny App R code to subset data in an unbiased fashion. Subsets were set at the same N across samples and retained representative average and standard deviation information. The method can be used for quantitation of entire fields of view or other replicates without biasing the data pool toward large N samples. We showed examples of the tool's use with fluorescence data and DNA-damage related Comet tail quantitation. This FairSubset tool and the method to retain distribution information at the single-datum level may be considered for standardized use in fair publishing practices.