The increasing use of large panel next-generation sequencing technologies in clinical settings has facilitated the identification of pan-cancer biomarkers, which can be diagnostic, prognostic, predictive, or most importantly, actionable.
To discuss recently approved and emerging pan-cancer and multihistology biomarkers as well as testing methodologies.
The US Food and Drug Administration approval documents, National Comprehensive Cancer Network guidelines, literature, and authors' own publications.
Since 2017, the US Food and Drug Administration has approved genotype-directed therapies for pan-cancer biomarkers, including microsatellite instability, neurotrophic receptor kinases fusions, and high-tumor mutation burden. Both the importance and rarity of these biomarkers have increased the prevalence of genomic profiling across solid malignancies. As an integral part of the management team of patients with advanced cancer, pathologists need to be aware of these emerging biomarkers, the therapies for which they determine eligibility, and the strengths and pitfalls of the available clinical assays.
Massively parallel or next-generation sequencing (NGS) of large panels of genes in all tumor types has amplified our knowledge about the prevalence of certain oncogenic alterations and played a large part in their detection for eligibility for specific genotype-directed therapies. Our previous report of mutational landscape of distinct histologically defined tumor types from 10 000 patients with metastatic solid cancers revealed recurrent targetable alterations across tumor types, including somatic mutations, copy number changes, and structural variants. At the time of the study, approximately 30% of these alterations were targetable, and 11% of these patients were enrolled in clinical trials based on their genomic profiling data.1 One such example is the fusions involving neurotrophic receptor kinases (NTRK) family genes 1-3, which have been identified in a diverse spectrum of adult and pediatric cancers. A clinical trial of the Trk inhibitor larotrectinib demonstrated marked and durable antitumor activity in these patients, regardless of tumor type.2 This led to the accelerated approval of larotrectinib as a tissue-agnostic treatment of cancers harboring NTRK fusions. In addition, biomarkers associated with immuno-oncology (IO) agents can be assessed through large-panel NGS testing, such as mismatch repair (MMR)/microsatellite instability (MSI) signature and tumor mutation burden (TMB).1 These 2 biomarkers were approved as pan-cancer biomarkers of pembrolizumab in 2017 and 2020, respectively.3 Patients without targetable oncogene alterations may benefit from IO therapy if their tumors are MSI-high (MSI-H) or TMB-H.
DNA-based massive parallel sequencing (DNAseq) with large panels can detect these pan-cancer biomarkers. There are 2 different chemistries employed in DNA-based NGS. Hybrid capture, which has the advantage of evaluation copy number alteration, structural variant but limitations of higher input DNA requirement and longer turnaround time, while amplicon capture has the advantage of low DNA input requirement and high sensitivity but limitation of more difficult copy number and structural variant assessment. DNAseq can be matched tumor-normal sequencing or tumor only. Matched tumor-normal sequencing has higher accuracy in evaluating TMB because it can unequivocally identify the somatic mutations in tumor cells, whereas tumor-only sequencing cannot distinguish rare germline variants and somatic mutations coming from white blood cells versus somatic mutations coming from tumor cells.4
Besides DNAseq, other methods are also available to detect these biomarkers, including immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), reverse-transcription polymerase chain reaction (RT-PCR), multiplex PCR, and RNA-based NGS, such as anchored multiplex PCR, which is especially useful for the detection of gene fusions arising from genomic breakpoints within very large introns that are difficult to cover by DNA NGS, such as fusions involving NTRK3.
Herein, we summarized the emerging pan-cancer biomarkers, multihistology biomarkers, and current testing technologies as an up-to-date review.
FDA-APPROVED PAN-CANCER BIOMARKERS
MSI is the first tissue/site-agnostic (pan-cancer) biomarker approved by the US Food and Drug Administration (FDA) and it is one of the most important biomarkers to predict response to immune checkpoint inhibitor therapies.1,3 The indications to test include adult and pediatric patients with unresectable or metastatic MSI-H or dMMR solid tumors that have progressed after prior treatment and who have no satisfactory alternative treatment options. Patients with solid malignancies should receive MSI status testing as part of a workup for either Lynch syndrome or pembrolizumab eligibility (see National Comprehensive Cancer Network tumor-specific guidelines).
Microsatellites are 1- to 6-base pair long short-tandem repeats scattered throughout the human genome. They are prone to replication errors induced by DNA polymerase slippage, which are corrected by the MMR proteins MLH1, PMS2, MSH2, and MSH6. MSI-H tumors result from deficient MMR (dMMR) and are usually hypermutated with a particularly elevated number of frame-shift indels. Previously, MSI was studied mainly in colorectal cancer (CRC) and uterine endometrioid cancer (UEC) due to the high prevalence of MSI-H status in these tumor types. MSI testing was performed mainly by multiplex PCR and evaluation of MMR protein expression was performed by IHC. Testing by MMR IHC and MSI PCR was recommended based on patient's age and family history according to the Bethesda guidelines.5 Patients with MSI-H/dMMR tumors have an increased chance of harboring Lynch Syndrome, which accounts for 3% to 5% of CRC, while somatic dMMR is responsible for approximately 15% of CRC.6 These patients have a lower response rate to fluorouracil and are eligible for pembrolizumab if their cancer is unresectable or metastatic.7–9 With the recognition of predictive value of MSI for IO therapy responses and given the high prevalence of dMMR in CRC, the updated 2020 National Comprehensive Cancer Network guidelines for CRC recommend universal MMR or MSI testing in all newly diagnosed patients with CRC. MMR or MSI testing is also included in 2020 National Comprehensive Cancer Network guidelines for locally advanced, recurrent, or metastatic gastroesophageal cancer, recurrent endometrial cancer, and many other cancer types, such as pancreatic cancer and cancer of unknown primary, which were discovered to have low frequencies of MSI-H through prospective testing by large-panel NGS.10
Features and characteristics of different MSI/MMR detection methods are summarized in Table 1, including IHC for MMR proteins11 ; multiplex PCR for microsatellite markers12 ; and software programs that use NGS data to determine MSI status, such as MANTIS (Microsatellite Analysis for Normal Tumor InStability, Ohio State University, https://github.com/OSU-SRLab/MANTIS), mSINGS (MSI phenotype using NGS, Ohio State University), and MSIsensor (Washington University in St. Louis, https://github.com/ding-lab/msisensor).13–15 Accepted testing material is formalin-fixed, paraffin-embedded (FFPE) tissue. Matched normal is often required in the form of DNA from blood or nontumor FFPE tissue. MMR IHC works better with low-tumor purity samples than PCR or NGS because the result is visualized rather than scraped off slides and diluted by normal DNA. MMR IHC has a fast turnaround time of approximately 1 to 2 days and uses only 4 unstained slides, whereas PCR or NGS requires more tissue material. MMR IHC has a sensitivity of approximately 94%.11,16 It has been documented that tumors with apparently normal MMR protein expression by IHC occasionally are MSI-H, and this is usually associated with pathogenic missense mutations in MMR genes (as opposed to truncating mutations resulting in loss of protein expression). MMR IHC is specific provided that normal internal controls demonstrate staining. One fairly common situation leading to false loss of MSH6 expression is the use of neoadjuvant chemotherapy.17 NGS-based MSI assessment programs, such as mSINGS, MANTIS, and MSIsensor, each requires validation when performed on custom NGS panels in a specific molecular lab.1,10,13,15,18 NGS requires at least 1 to 2 weeks in terms of turnaround time but provides other important data, such as MAPK pathway alterations and TMB.
Neurotrophic Receptor Kinases Fusions
NTRK fusion (neurotrophic receptor kinases) is the second tissue/site-agnostic (pan-cancer) biomarker approved by the FDA and it can predict response to Trk inhibitors. The indications to test are unresectable or metastatic solid malignancies (see National Comprehensive Cancer Network guidelines).
The NTRK family includes 3 genes, NTRK1, NTRK2, and NTRK3, encoding the receptor tyrosine kinases NTRK1, NTRK2, and NTRK3 (also known as, TrkA, TrkB, and TrkC, respectively). Physiologically, they play important roles in cell proliferation and survival and are expressed in neural and smooth muscle tissues. In-frame fusions of the C-terminal of NTRK with the N-terminal of partner genes activate the kinase domain and become novel targets of tyrosine kinase inhibitors (TKIs). While NTRK fusions are rare (<1%) in all solid tumors, they are very prevalent in certain tumors as follows: secretory carcinomas of the breast and salivary gland as well as infantile fibrosarcomas and congenital mesoblastic nephromas (>90%); intermediate frequency (5%–25%) in papillary thyroid carcinoma and spitzoid tumors; while low frequency (<5%) in appendiceal cancer, glioma/glioblastoma, gastrointestinal stromal tumor, non-small cell lung cancer (NSCLC), and so on.19,20 Patients with NTRK fusions demonstrated a response rate of more than 75% with long duration to larotrectinib regardless of 5′ partner and across many histologies.2 NTRK fusion can be performed on FFPE tissue by IHC, break-apart FISH, RT-PCR, DNA-based NGS for NTRK 1/2 fusions and ETV6-NTRK3 fusions, RNA-based NGS for all NTRK fusions, or DNA/RNA hybrid NGS (Table 2).21–26
Like MMR IHC, pan-TRK IHC has a quick turnaround time and works well for low-tumor purity cases, yet its sensitivity is lower for NTRK3 fusions (approximately 77%) and its specificity is lower in tumors with neural and/or smooth muscle differentiations.22,27,28 DNA-based NGS works well if the regions of interest can be appropriately covered (in this case, both introns and exons of NTRK1-3 spanning common breakpoints). NTRK3 has proven difficult to cover sufficiently due to long and repetitive introns and thus, the sensitivity of DNA-based NGS is lower for NTRK3 fusions. RNA-based NGS has the best sensitivity and specificity assuming satisfactory quality RNA is available. NTRK break-apart FISH has shorter turnaround time than NGS and requires only 3 unstained slides (1 per gene). It can only tell whether a NTRK gene rearrangement is present but does not identify the precise oncogenic fusion.
Tumor Mutation Burden
Recently, the FDA approved pembrolizumab for adults and children with tumor mutation burden-high (TMB-H) solid tumors (≥10 mutations/megabase), unresectable or metastatic solid tumors, based on the ongoing phase 2 KEYNOTE-158 trial. In this trial, the overall response rate was 28.3% for TMB-H and 6.5% for TMB-low tumors.29 This approval marked the second tumor-agnostic approval for pembrolizumab and defined TMB as the third pan-cancer biomarker.
TMB is a continuous, quantitative variable that is associated with the likelihood of tumor cell neoantigen generation. It is defined as the total number of nonsynonymous mutations per megabase of tumor genome. Even though not all the mutations generate neoantigens, the total number of mutations in a given tumor correlates with the odds of developing neoantigens and responding to immunotherapy. Therefore, TMB had emerged as a promising biomarker of response to IO therapies in several prospective trials, including multiple tumor types.30,31
On the other hand, the predictive value of TMB varies among tumors and may not correlate with response to IO agents in certain tumor types. One example is Merkel cell carcinoma. In Merkel cell carcinoma, the response rates to IO agents are not statistically different (P = .63) between TMB-H group, which exhibited an ultraviolet light exposure mutational signature (50%) and TMB low group, which showed positive Merkel cell polyomavirus (41%).32 Other factors may also affect the predictive value of TMB. In NSCLC, mutations of EGFR and STK11 are associated with poor response to immune checkpoint inhibitors.33 In general, host response or genomic aberrations affecting specific immune-signaling pathways or leading to immune dysregulation, such as loss-of-function mutations in beta-2 microglobulin or loss of human leukocyte antigen genes, PTEN loss, or mutations in JAK or other IFNγ-related genes have been associated with resistance to immune checkpoint inhibitors.34–38 All of these should be considered when selecting patients for IO therapy.
While whole-exome sequencing is the optimal method to estimate TMB, targeted large panel NGS testing has been demonstrated to be comparable for the estimation of TMB.1,39 However, the value of TMB varies among different panels and is impacted by assay design (tumor-normal matched sequencing or tumor only), panel size, genome coverage, and bioinformatics pipelines to calculate TMB (nonsynonymous only or both nonsynonymous and synonymous, and so on). Tumor-normal matched sequencing can eliminate rare germline variants and somatic mutations from white blood cells (clonal hematopoiesis),4 while the value of TMB, based on tumor only sequencing, may be compounded by these alterations.
TMB predicts response to IO therapy and the indications to test are all advanced solid malignancies as eligibility criterion for pembrolizumab. TMB can be tested by targeted panel or whole-exome sequencing. The FDA cleared Omics Core whole-exome sequencing as an in-vitro diagnostic test, reporting overall TMB and the FDA approved the FoundationOne CDx (Foundation Medicine) assay as a companion diagnostic for pembrolizumab to identify patients with TMB-H malignancies on FFPE tissue with a TMB-H cutoff is 10 or more mutations/megabase. Selected testing methods are summarized in Table 3.
FUTURE CANDIDATES OF PAN-CANCER BIOMARKERS
Programmed Death-Ligand 1 Expression
The interaction between programmed death protein 1 (PD-1) and its ligand (PD-L1) is a well-characterized immune checkpoint. PD-L1 expression on tumors affects neoantigen presentation and the level of PD-L1 expression on tumor cells or immune cells in the tumor microenvironment is associated with clinical responses to IO therapies in many tumor types. The FDA approved 4 PD-L1 IHC monoclonal antibodies to test PD-L1 expression on FFPE tissue samples and several immune checkpoint inhibitors for certain cancer types. The approval list continues to expand to more tumor types in recent years.
PD-L1 IHC reporting systems are based on either PD-L1–stained tumor cells (TC) or PD-L1–stained tumor infiltrating immune cells (IC), depending on the tumor types (Table 4). PD-L1 expression on TC was evaluated as tumor proportion score or percentage of TC, which is the percentage of PD-L1–positive TC showing partial or complete membrane staining in the overall tumor sections; PD-L1 expression on IC was assessed as the proportion of tumor area occupied by PD-L1–positive IC of any intensity,40 while combined positive score is the number of PD-L1–staining cells (tumor cells, lymphocytes, macrophages) divided by the total number of viable tumor cells, multiplied by 100.41
Although PD-L1 expression, MSI, and TMB are all biomarkers that determine eligibility for IO therapies, the correlation between PD-L1 expression and treatment response varies; most studies have found little or no correlation between TMB and PD-L1 expression29 and the overlap between these markers varies among different tumor types.42 Patients with elevated PD-L1 levels may not respond to immunotherapy, while a substantial minority of patients who had low PD-L1 expression may experience clinical benefit.31 In a study of comparison of MSI status, PD-L1, and TMB in 11 348 patients, only 0.6% of patients were positive for all 3 of them. Therefore, it is important to perform comprehensive assessment of these biomarkers to select the patients most likely to respond to IO therapies.
Rearranged During Transfection Fusions and Mutations
The RET gene, a gene name derived from “rearranged during transfection,” is mutated in approximately 80% of medullary thyroid cancer, and fusions have been detected in papillary thyroid carcinoma, NSCLC, and a range of other tumor types at lower frequencies.43–46 The overall detection rate of RET fusions in NSCLC is 1% to 2% but fusions are enriched in nonsmokers lacking other known driver mutations.47,48 RET fusions define a new therapeutic target in this subset of lung cancers, especially with the availability of selective RET inhibitor selpercatinib, which demonstrated durable response and increased progression-free survival.49,50 In NSCLC, the overall response rate was 64% in previously treated patients and as high as 84% in never-treated patient group. In medullary thyroid cancer, the overall response rate of selpercatinib for the 55 previously treated patients was 69% and 73% in the patients without prior treatments. In RET fusion-positive thyroid cancer, the overall response rate for the 19 previously treated patients was 79% and 100% patients without prior treatments. Most patients showed responses longer than 6 to 12 months.50,51 Based on these clinical trials, Retevmo (selpercatinib) was recently approved by the FDA for the treatment of RET fusion-positive NSCLC, RET fusion-positive thyroid cancer, and RET-mutant medullary thyroid cancer.52,53
Testing of RET mutations and fusions is indicated in NCSLC and thyroid cancers and the available testing methods on FFPE tissue are listed in Table 5.
Fibroblast Growth Factor Receptor
Fibroblast growth factor receptor (FGFR) is a family of transmembrane tyrosine kinase receptors. They dimerize when binding with ligands, fibroblast growth factors (FGF), leading to intracellular phosphorylation of receptor kinase domains, triggering a cascade of intracellular signaling, and gene transcription. FGF/FGFRs signal through several downstream intracellular pathways, including the Ras/Raf/MEK and the phosphatidylinositol-4,5-bisphosphate 3 kinase (PI3K)–Akt pathway. In solid tumors, FGFR abnormalities are mainly copy number amplification, then gain of function mutations, and less common structural rearrangements. Urothelial carcinoma has the highest overall prevalence of FGFR alterations, followed by breast carcinoma, endometrial adenocarcinoma, ovarian carcinoma, glioma, squamous cell lung carcinoma, gastric adenocarcinoma, cholangiocarcinoma, and so on.54 FGFR3 alteration by RT-PCR has been approved in metastatic urothelial carcinoma. FGFR2 gene fusions are common in intrahepatic cholangiocarcinoma, ranging from 10% up to 43% of cases. FGFR2 fusion detection in cholangiocarcinoma was part of companion diagnostics of FoundationOne CDx FDA approval.
Other tumor types with FGFR2 alterations are breast, gastrointestinal tract, and lung cancers, suggesting that FGFR could be another pan-cancer biomarker. The FDA approved the pan-FGFR inhibitor Balversa (erdafitinib) for locally advanced or metastatic bladder cancer in 2019 and a more selective FGFR inhibitor, pemigatinib, for cholangiocarcinoma with an FGFR2 fusion in 2020.
Testing for FGFR fusions can be performed with DNAseq, RNAseq, FISH, or RT-PCR, while mutations can be tested by DNAseq and RT-PCR.
Pan-cancer and multihistology biomarkers are new in the field of molecular testing and treatment. Large-panel comprehensive genomic profiling has made it possible to screen for various rare targetable alterations simultaneously across all histologies. The list of targetable alterations continues to grow along with the list of FDA-approved biomarkers used for various tumor histologies. It is therefore important to not only know which biomarkers are used for guiding management, but also the advantages and pitfalls of the assays used to assess them.
Ladanyi received funding support from Loxo Oncology at Lilly and advisory board compensation from Bayer and Merck. Hechtman received research funding from Bayer and Eli Lilly as well as honoraria/consulting fees from Axiom Healthcare Strategies, WebMD, and Illumina.
The other authors have no relevant financial interest in the products or companies described in this article.