Swapnil Potdar

Mr. Swapnil Potdar

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 November 2021 in Cancer Discovery
Verified
Journal Article
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DMDisha Malani
Disha Malani
AKAshwini Kumar
Ashwini Kumar
OBOscar Brück
Oscar Brück
MKMika Kontro
Mika Kontro
BYBhagwan Yadav
Bhagwan Yadav
KPKimmo Porkka
Kimmo Porkka
We generated ex vivo drug-response and multiomics profiling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identification of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profiling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. Significance: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes significant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB. See related commentary by Letai, p. 290. This article is highlighted in the In This Issue feature, p. 275

9 December 2019 in Nature Machine Intelligence
Verified
Journal Article
Closed access
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AIAleksandr Ianevski
Aleksandr Ianevski
AGAnil K. Giri
Anil K. Giri
PGPrson Gautam
Prson Gautam
AKAlexander Kononov
Alexander Kononov
SPSwapnil Potdar
Swapnil Potdar
TATero Aittokallio
Tero Aittokallio

1 June 2020 in Bioinformatics
Verified
Journal Article
Open access
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SPSwapnil Potdar
Swapnil Potdar
AIAleksandr Ianevski
Aleksandr Ianevski
JMJohn-Patrick Mpindi
John-Patrick Mpindi
DBDmitrii Bychkov
Dmitrii Bychkov
CFClément Fiere
Clément Fiere
PÖPäivi Östling
Päivi Östling
High-throughput screening (HTS) enables systematic testing of thousands of chemical compounds for potential use as investigational and therapeutic agents. HTS experiments are often conducted in multi-well plates that inherently bear technical and experimental sources of error. Thus, HTS data processing requires the use of robust quality control procedures before analysis and interpretation. Here, we have implemented an open-source analysis application, Breeze, an integrated quality control and data analysis application for HTS data. Furthermore, Breeze enables a reliable way to identify individual drug sensitivity and resistance patterns in cell lines or patient-derived samples for functional precision medicine applications. The Breeze application provides a complete solution for data quality assessment, dose–response curve fitting and quantification of the drug responses along with interactive visualization of the results. The Breeze application with video tutorial and technical documentation is accessible at https://breeze.fimm.fi; the R source code is publicly available at https://github.com/potdarswapnil/Breeze under GNU General Public License v3.0. swapnil.potdar@helsinki.fi Supplementary data are available at Bioinformatics online.

25 June 2019 in BMC Cancer
Verified
Journal Article
Open access
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ESErlend Skaga
Erlend Skaga
EKEvgeny Kulesskiy
Evgeny Kulesskiy
AFArtem Fayzullin
Artem Fayzullin
CSCecilie Jonsgar Sandberg
Cecilie Jonsgar Sandberg
SPSwapnil Potdar
Swapnil Potdar
EVEinar O. Vik-Mo
Einar O. Vik-Mo
A major barrier to effective treatment of glioblastoma (GBM) is the large intertumoral heterogeneity at the genetic and cellular level. In early phase clinical trials, patient heterogeneity in response to therapy is commonly observed; however, how tumor heterogeneity is reflected in individual drug sensitivities in the treatment-naïve glioblastoma stem cells (GSC) is unclear. We cultured 12 patient-derived primary GBMs as tumorspheres and validated tumor stem cell properties by functional assays. Using automated high-throughput screening (HTS), we evaluated sensitivity to 461 anticancer drugs in a collection covering most FDA-approved anticancer drugs and investigational compounds with a broad range of molecular targets. Statistical analyses were performed using one-way ANOVA and Spearman correlation. Although tumor stem cell properties were confirmed in GSC cultures, their in vitro and in vivo morphology and behavior displayed considerable tumor-to-tumor variability. Drug screening revealed significant differences in the sensitivity to anticancer drugs (p < 0.0001). The patient-specific vulnerabilities to anticancer drugs displayed a heterogeneous pattern. They represented a variety of mechanistic drug classes, including apoptotic modulators, conventional chemotherapies, and inhibitors of histone deacetylases, heat shock proteins, proteasomes and different kinases. However, the individual GSC cultures displayed high biological consistency in drug sensitivity patterns within a class of drugs. An independent laboratory confirmed individual drug responses. This study demonstrates that patient-derived and treatment-naïve GSC cultures maintain patient-specific traits and display intertumoral heterogeneity in drug sensitivity to anticancer drugs. The heterogeneity in patient-specific drug responses highlights the difficulty in applying targeted treatment strategies at the population level to GBM patients. However, HTS can be applied to uncover patient-specific drug sensitivities for functional precision medicine.

9 November 2020 in Leukemia
Verified
Journal Article
Open access
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SAShady Adnan-Awad
Shady Adnan-Awad
DKDaehong Kim
Daehong Kim
HHHelena Hohtari
Helena Hohtari
KJKomal Kumar Javarappa
Komal Kumar Javarappa
TBTania Brandstoetter
Tania Brandstoetter
SMSatu Mustjoki
Satu Mustjoki
The oncogenic protein Bcr-Abl has two major isoforms, p190Bcr-Abland p210Bcr-Abl. While p210Bcr-Ablis the hallmark of chronic myeloid leukemia (CML), p190Bcr-Abloccurs in the majority of Philadelphia-positive acute lymphoblastic leukemia (Ph + ALL) patients. In CML, p190Bcr-Abloccurs in a minority of patients associating with distinct hematological features and inferior outcomes, yet the pathogenic role of p190Bcr-Abland potential targeting therapies are largely uncharacterized. We employed next generation sequencing, phospho-proteomic profiling, and drug sensitivity testing to characterize p190Bcr-Ablin CML and hematopoietic progenitor cell line models (Ba/f3 and HPC-LSK). p190Bcr-AblCML patients demonstrated poor response to imatinib and frequent mutations in epigenetic modifiers genes. In contrast with p210Bcr-Abl, p190Bcr-Ablexhibited specific transcriptional upregulation of interferon, interleukin-1 receptor, and P53 signaling pathways, associated with hyperphosphorylation of relevant signaling molecules including JAK1/STAT1 and PAK1 in addition to Src hyperphosphorylation. Comparable to p190Bcr-AblCML patients, p190Bcr-Ablcell lines demonstrated similar transcriptional and phospho-signaling signatures. With the drug sensitivity screening we identified targeted drugs with specific activity in p190Bcr-Ablcell lines including IAP-, PAK1-, and Src inhibitors and glucocorticoids. Our results provide novel insights into the mechanisms underlying the distinct features of p190Bcr-AblCML and promising therapeutic targets for this high-risk patient group.

9 October 2019 in The Journal of Pathology
Verified
Journal Article
Closed access
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KKKatja Kaipio
Katja Kaipio
PCPing Chen
Ping Chen
PRPia Roering
Pia Roering
KHKaisa Huhtinen
Kaisa Huhtinen
PMPiia Mikkonen
Piia Mikkonen
OCOlli Carpen
Olli Carpen