Molecular Biology of Osteosarcoma

Osteosarcoma (OS) is the most frequent primary bone cancer in children and adolescents and the third most frequent in adults. Many inherited germline mutations are responsible for syndromes that predispose to osteosarcomas including Li Fraumeni syndrome, retinoblastoma syndrome, Werner syndrome, Bloom syndrome or Diamond–Blackfan anemia. TP53 is the most frequently altered gene in osteosarcoma. Among other genes mutated in more than 10% of OS cases, c-Myc plays a role in OS development and promotes cell invasion by activating MEK–ERK pathways. Several genomic studies showed frequent alterations in the RB gene in pediatric OS patients. Osteosarcoma driver mutations have been reported in NOTCH1, FOS, NF2, WIF1, BRCA2, APC, PTCH1 and PRKAR1A genes. Some miRNAs such as miR-21, -34a, -143, -148a, -195a, -199a-3p and -382 regulate the pathogenic activity of MAPK and PI3K/Akt-signaling pathways in osteosarcoma. CD133+ osteosarcoma cells have been shown to exhibit stem-like gene expression and can be tumor-initiating cells and play a role in metastasis and development of drug resistance. Although currently osteosarcoma treatment is based on adriamycin chemoregimens and surgery, there are several potential targeted therapies in development. First of all, activity and safety of cabozantinib in osteosarcoma were studied, as well as sorafenib and pazopanib. Finally, novel bifunctional molecules, of potential imaging and osteosarcoma targeting applications may be used in the future

Career and Professional Development for Young Oncologists

Young oncologists around the globe face many challenges when it comes to their career and professional development. Aspects such as time management, work-life balance, career progression, and educational opportunities are only some of them. Professional societies have identified these challenges in this professional group and have designed programs to tackle them specifically. The importance of this strategy cannot be overstated, as young oncologists, defined by most societies as oncologists under 40 years of age, compose almost 50% of the oncology workforce. On the other hand, recent surveys have shown that many young oncologists are considering alternative career paths due to burnout issues aggravated by the COVID-19 pandemic, on top of all other challenges. The virtual setting that has been forcedly introduced into our professional life has shortened distances between professionals and might have contributed to more accessible access to information and opportunities that some young oncologists could not profit from due to their traveling constraints. On the other hand, this virtual setting has shown us the asymmetries in opportunities for these professionals. Knowledgeable of all this, we summarize in this article some of the career and professional development offer available to all young oncologists, which we consider could help them deal with current and future challenges

An interpretable AI model for recurrence prediction after surgery in gastrointestinal stromal tumour: an observational cohort studyResearch in context

Summary: Background: There are several models that predict the risk of recurrence following resection of localised, primary gastrointestinal stromal tumour (GIST). However, assessment of calibration is not always feasible and when performed, calibration of current GIST models appears to be suboptimal. We aimed to develop a prognostic model to predict the recurrence of GIST after surgery with both good discrimination and calibration by uncovering and harnessing the non-linear relationships among variables that predict recurrence. Methods: In this observational cohort study, the data of 395 adult patients who underwent complete resection (R0 or R1) of a localised, primary GIST in the pre-imatinib era at Memorial Sloan Kettering Cancer Center (NY, USA) (recruited 1982–2001) and a European consortium (Spanish Group for Research in Sarcomas, 80 sites) (recruited 1987–2011) were used to train an interpretable Artificial Intelligence (AI)-based model called Optimal Classification Trees (OCT). The OCT predicted the probability of recurrence after surgery by capturing non-linear relationships among predictors of recurrence. The data of an additional 596 patients from another European consortium (Polish Clinical GIST Registry, 7 sites) (recruited 1981–2013) who were also treated in the pre-imatinib era were used to externally validate the OCT predictions with regard to discrimination (Harrell's C-index and Brier score) and calibration (calibration curve, Brier score, and Hosmer-Lemeshow test). The calibration of the Memorial Sloan Kettering (MSK) GIST nomogram was used as a comparative gold standard. We also evaluated the clinical utility of the OCT and the MSK nomogram by performing a Decision Curve Analysis (DCA). Findings: The internal cohort included 395 patients (median [IQR] age, 63 [54–71] years; 214 men [54.2%]) and the external cohort included 556 patients (median [IQR] age, 60 [52–68] years; 308 men [55.4%]). The Harrell's C-index of the OCT in the external validation cohort was greater than that of the MSK nomogram (0.805 (95% CI: 0.803–0.808) vs 0.788 (95% CI: 0.786–0.791), respectively). In the external validation cohort, the slope and intercept of the calibration curve of the main OCT were 1.041 and 0.038, respectively. In comparison, the slope and intercept of the calibration curve for the MSK nomogram was 0.681 and 0.032, respectively. The MSK nomogram overestimated the recurrence risk throughout the entire calibration curve. Of note, the Brier score was lower for the OCT compared to the MSK nomogram (0.147 vs 0.564, respectively), and the Hosmer-Lemeshow test was insignificant (P = 0.087) for the OCT model but significant (P 50% risk of recurrence. Interpretation: We present the first prognostic models of recurrence risk in GIST that demonstrate excellent discrimination, calibration, and clinical utility on external validation. Additional studies for further validation are warranted. With further validation, these tools could potentially improve patient counseling and selection for adjuvant therapy. Funding: The NCI SPORE in Soft Tissue Sarcoma and NCI Cancer Center Support Grants