Abstract 2012: Recurrent rearrangements of NAALADL2 in prostate, breast, cervical, head and neck and lung squamous cell carcinoma
Bibliographic record
Abstract
Abstract Prostate cancer is a heterogeneous disease with unique molecular aberrations present in patient sub-groups. Distinct prostate cancer molecular changes have been shown to associate with specific clinical outcomes, suggesting the potential of molecular markers as diagnostic and prognostic biomarkers for prostate cancer. Recurrent ETS family gene fusions, BRAF and SPINK1 overexpression account for about 50-60% of the prostate cancer cases. Genetic aberrations in the remaining 40-50% of the cases is not known. Our attempt to identify new molecular markers in prostate cancer led to the identification of NAALADL2 gene shown to be associated with aggressive prostate cancer. In this study, we carried out a comprehensive analysis of genomic changes of NAALADL2 in prostate and other solid cancers by analyzing copy number changes and gene expression using TCGA next generation RNA sequencing data. We observed recurrent amplification, rearrangement, deletion, mutations and over-expression of NAALADL2 in prostate cancer cases. Notably, we observed mutually exclusive aberrations in NAALADL2 when compared to other cases with known prostate cancer aberrations including ETS gene fusions, indicating NAALADL2 as a distinct molecular sub-set of prostate cancer. Independent validation by fluorescent in situ hybridization (FISH) analysis using break apart probe for NAALADL2 on 874 prostate cancer revealed recurrent amplification and rearrangements in about 8% (71/874) [PN1] of the cases with higher prevalence in Caucasian American than African American cases. Based on these results, we explored prostate cancer TGCA gene fusion database and identified additional cases with gene fusions involving NAALADL2. We selected one of the gene fusions identified in the TCGA database involving NAALADL2-PIK3CA and conducted in vitro functional characterization studies and showed its oncogenic properties. Gene expression microarray analysis of RWPE1 cells transfected with NAALADL2-PIK3CA showed dysregulation of genes involved in cancer related pathways, further suggesting a role for NAALADL2-PIK3CA in prostate cancer development. Based on these studies, we explored the incidence of NAALADL2 gene fusion in other solid cancers including lung squamous cell cancer (LUSC), ovarian cancer, head and neck cancer, cervical cancer and breast cancer shown to have recurrent gene fusions identified in the TCGA gene fusion database. Notably, recurrent rearrangements and amplification are seen in a large subset (45%) of LUSC patients, but not in lung adenocarcinoma, suggesting that NAALADL2 could be developed as a novel biomarker in LUSC. Further validation studies using FISH in our independent cohort of LUSC and breast cancer patients including 79 patients from Ghana confirmed recurrent rearrangements and amplification in a subset of cases. In conclusion, similar to ERG, BRAF and FGFR genes, we show recurrent gene fusions of NAALADL2 across multiple solid cancer with potential applications as a pan cancer molecular marker for cancer diagnosis and a potential target for drug development. Citation Format: Pavithra D. Arachchige, Shannon Carskadon, James Hu, Justin Fernando, Darshan S. Chandrashekar, Nilesh S. Gupta, Sean R. Williamson, Dhananjay A. Chitale, Craig G. Rogers, James O. Peabody, Mani Menon, Tarek A. Bismar, Evelyn Jiagge, Sooryanarayana Varambally, Nallasivam Palanisamy. Recurrent rearrangements of NAALADL2 in prostate, breast, cervical, head and neck and lung squamous cell carcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2012.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".