Kedar Hastak, MS, PhD
Field Applications Scientist

Synthetic Lethality: Therapeutically exploiting this mechanism and discovering biomarkers of response

Basics of DNA Repair Pathways

DNA repair processes are essential to preserve genomic integrity from both exogenous and endogenous DNA damage. These repair processes exist in prokaryotic and eukaryotic organisms and many of the proteins involved have been highly conserved throughout mammalian evolution.

Various DNA repair pathways (Figure 1) including base excision repair (BER), nucleotide excision repair (NER), and mismatch repair (MMR) address single-stranded breaks, bulky lesions, and mismatches. On the other hand, double-stranded breaks (DSBs) are repaired by homologous recombination repair (HRR) and non-homologous end joining (NHEJ). HRR is the primary double-stranded break repair mechanism except in homologous recombination deficient cells, such as those with BRCA 1/2 mutations, where DNA damage is repaired with low fidelity repair mechanisms like NHEJ.

Figure 1: From Postel-Vinay et al. 2012. The potential of exploiting DNA-repair defects for optimizing lung cancer treatment, Nature Reviews Clinical Oncology volume 9, pages144–155(2012)

HRR is orchestrated by several important proteins such as H2AX, ATR, ATM, BRAC1, BRAC2, RAD51. Tumors with HRR deficiency (HRD) were originally described in cancers that had germline BRCA1 and BRCA2 mutations (Venkitaraman AR. Linking the cellular functions of BRCA genes to cancer pathogenesis and treatment. Annu Rev Pathol.2009;4:461–487). However, genetic and epigenetic inactivation of other HR components can also lead to HRD in sporadic cancers, which is broadly termed as ‘BRCAness’ (Turner N, Tutt A, Ashworth A. Hallmarks of ‘BRCAness’ in sporadic cancers. Nat Rev Cancer. 2004;410:814–819. and Lord CJ, Ashworth A. BRCAness revisited. Nat Rev Cancer. 2016;162:110–120). Recently, the DNA repair enzymes poly-ADP ribose polymerase 1 (PARP1) and PARP2 have gained importance in treating tumors with germline BRCA mutations. The FDA has approved the use of various PARP inhibitors (PARPi) for the treatment of ovarian, prostate, pancreatic, fallopian tube, and peritoneal cancers. The sensitivity of such tumors to PARP inhibition is directly related to the concept of synthetic lethality. Recently, the FDA granted Lynparza (Olaparib) breakthrough therapy designation for the treatment of BRCA1/2 or ATM gene mutated metastatic castration resistant prostate cancer.

Synthetic Lethality

What is synthetic lethality?

Synthetic lethality is defined as a type of genetic interaction in which the co-occurrence of two genetic events results in organismal or cellular death. Drugs can induce synthetic lethal genetic interactions as well.  One very common example is the utilization of PARP inhibitors to treat tumors that harbor a pre-existing defect in HR-related pathways. Additionally, our expanding knowledge of drug-gene synthetic lethal interactions may also enable us to design various combination therapies and predict synergistic/sensitizer combinatorial treatment regimens. This can be particularly important in limiting drug resistance and enabling the administration of each drug at lower concentrations to achieve the same biological effect, thus potentially reducing drug toxicity and limiting side effects.

Advances in predictive biomarkers and progress in both targeted and immunotherapies have brought about substantial and promising clinical results. However, new strategies for untreatable target genes, better understanding of overcoming resistance to molecularly-targeted therapy and immunotherapies along with identification of new continuous variable biomarkers to better predict response to immunotherapies are needed to advance the field of precision medicine. Synthetic lethality is one of the many approaches that is currently being considered to identify more novel therapeutic options.

Synthetic Lethality and Genomics

At a high level, mutations in cancer genes may be classified into loss-of-function (mostly in tumor suppressor genes) or gain-of-function defects (predominantly in oncogenes). While synthetic lethality interactions are more commonly associated with loss-of-function alleles, it can also apply to gain-of-function alleles as well. As stated earlier, the most common example cited for synthetic lethality is between the loss-of-function tumor suppressor BRCA genes and the PARP enzyme. In this case, patients harboring these mutations benefit from inhibition of PARP. However, there is also a need to investigate gain-of-function treatments. Initial synthetic lethality studies involved RNAi or chemical library screening, yet they often have shown limited translational value. Recently, Lee et al. (Lee, J. S. et al.  Nat Commun  9, 2546, doi:10.1038/s41467-018-04647-1 (2018)), demonstrated the effective use of a genome-wide computational predcative model, ISLE (Identification of clinically-relevant Synthetic Lethality). The ISLE model showed that only a small subset of synthetic lethal gene candidates that were identified from in vitro screens were also associated with patient prognosis in a TCGA cohort. Moreover, the same group (Figure taken from Sahu, A. D. et al. Mol Syst Biol  15, e8323, doi:10.15252/msb.20188323 (2019)) also demonstrated that genomic and clinical survival data can be combined to identify synthetic rescue (SR) interactions (Figure 2). SR interactions denote a specific type of genetic interaction where a change in the activity of one gene reduces the cell’s fitness but an alteration of another gene (termed the SR partner) rescues cell viability (e.g., the rescue of Myc alterations by BCL2 activation in lymphomas). When a gene is targeted by a small molecule inhibitor or an antibody, the tumor may respond by changing the activity of the rescuer gene(s), conferring resistance to therapies.

Figure 2: Mol Syst Biol, Vol: 15, Issue: 3, First published: 12 March 2019, DOI: (10.15252,msb.20188323)

Recently Lee’s team performed a retrospective analysis of the WINTHER trial data. The WINTHER trial was the first large-scale basket clinical trial to incorporate transcriptomics data for cancer therapy in patients with advanced solid tumors. The patients were assigned to therapy on the basis of DNA sequencing as well as RNA expression. Overall, 303 patients consented; but only 107 (35%; 69 in arm A and 38 in arm B) were evaluable for therapy. The most common diagnoses were colon, head and neck, and lung cancers. Among the 107 patients, the rate of stable disease was ≥6 months while partial or complete response rate was 26.2%. They then applied the same genetic interaction models as described in the previously-mentioned publications and showed that by targeting synthetic lethal vulnerabilities in patients’ tumors identified by transcriptomic profiling, beneficial response rates could be as high as ~85%. The authors also applied this synthetic lethality-based approach on different targeted therapies across various cancer indications from publicly available data that was inclusive of pre-treatment transcriptomic data and clinical outcomes information. They concluded that synthetic lethality genetic interactions of the drug target genes can serve as effective biomarkers for predicting drug response in many cancer types. The authors also evaluated response to checkpoint inhibitors and used protein expression levels of PD-1 and CTLA-4 in TCGA data to identify the synthetic lethality and synthetic rescue partners of the respective checkpoint genes. They were able to identity statistically-significant synthetic rescue interactions, but not for synthetic lethality partners of PD-1 and CTLA-4.

The power of both DNA and RNA data

These recent studies demonstrate that whole exome sequencing (WES) and whole transcriptome sequencing (WTS) are powerful tools that can significantly benefit the field of precision medicine. As we know, tumors are quite complicated and typically have multiple changes at both the DNA and RNA level helping them to grow and metastasize. Thus, it is essential to investigate both. Furthermore, identifying clinically-relevant synthetic lethality or rescue interactions can play an important role in identifying acquired drug resistance mechanisms, especially in checkpoint inhibitor treatments. WES can identify germline and somatic mutations in genes involved in DNA repair pathways to identify the ‘BRCAness’ phenotype or mutations in MMR (MSI status). WES can also be utilized to study copy number variation and loss of heterozygosity which can be combined with mutations in BRCA (either germline or somatic) to identify tumors that may benefit from PARP inhibitors. Similarly, WTS can help create precise gene expression signatures that can be attributed to both primary and adaptive resistance in patients.

At Personalis, our ImmunoID NeXT Platform® represents an end-to-end solution for immuno-oncology and all precision oncology applications. It combines the pioneering ImmunoID NeXT Platform® assay, which employs enhanced WES and WTS, with sophisticated analytical engines to provide researchers with comprehensive genomic/transcriptomic data to accelerate their biomarker discovery programs. As shown in Figure 3, the unique design of the assay and analytical algorithms deliver critical tumor- and immune-related information including, but not limited to:

  • T-cell receptor (TCR) alpha & beta repertoire
  • Neoantigen detection and neoantigen load
  • Tumor mutational burden (TMB)
  • Microsatellite instability (MSI) characterization
  • Human leukocyte antigens (HLA) typing, HLA and beta-2 microglobulin (B2M) somatic mutations, and HLA loss of heterozygosity (LOH)
  • Tumor escape and resistance mechanisms
  • Oncoviral detection
Figure 3

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