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Latest Developments in Precision Medicine

Explore recent advances—from diagnostic technologies to novel biomarkers aiming to transform precision medicine.

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Digital Pathology Adoption Is Growing Due to a Number of Advantages

Computerized workflows and digitized image analysis are helping healthcare providers interpret complex data, creating personalized solutions for patients.1–3

Digital pathology may provide several benefits in precision medicine, including:

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  • Increased diagnostic accuracy and predictivity compared to traditional pathology methods4
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  • Paperless transmission of digital slides to and from members of the multidisciplinary team (MDT), reducing chances of misidentification or transposition errors5
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  • Optimization of workflow through quick and efficient tracking5
  • Transfer of slides and diagnostic information from laboratory to pathologist5
2 computers interacting icon

By using digital pathology, you can reduce persistent diagnostic testing challenges and provide faster delivery of results.5

MDT, multidisciplinary team.

Combine Digital Pathology With Computational Pathology for Enhanced Insights

When used with digital pathology, computational pathology extracts and analyzes complex data sets of pathology images to potentially improve workflow efficiencies and diagnostic quality.6,7 Combine digital pathology with genomic, clinical, and other data for novel diagnostic insights.

TechnologyBenefit in practice

Computational pathology

Incorporates multiple channels of data (e.g., demographics, digital pathology, multi-omics, lab results) into mathematic models.6,8

  • More accurate diagnosis and prognosis of personalized treatment6,8–10
  • Simplifying prostate cancer identification through the first FDA-approved artificial intelligence (AI) product in digital pathology11

Deep learning

With whole slide imaging, deep learning models in computational pathology are trained to detect malignancies and classify histology subtypes.8

  • Predicting lung tumor biomarkers and breast HER2 status3,12
  • Simplifying feature definition13
  • Recognizing complex objects more effectively, and saving time through parallel computation13,14
  • Widely used to develop patient outcome prediction models in lung cancer prognosis studies3

Radiomics

Integrating AI-driven pathology image analysis with radiomics to bridge medical imaging and precision medicine.8

  • More effectively identify the most significant clinical, pathological, and molecular features, leading to improved diagnosis and prognosis13

AI, artificial intelligence; FDA, US Food and Drug Administration; HER2, human epidermal growth factor receptor 2.

Diagnostic Advancements Are Improving Cancer Diagnosis and Care


Cancer diagnosis is often made at advanced stages where treatment choices are limited. Molecular biomarkers have spearheaded advancements in early cancer detection, with emerging methods geared towards further improving detection and monitoring.15

Infographic stating that if successfully scaled up, MCED could lower cancer-related deaths by 26 percent

When modelling for maximum benefit,
the use of MCED may result
in a relative

26%18,a

mortality reduction

Detect more cancers at treatable stages with multi-cancer early detection (MCED) screening

MCED is an investigational blood-based analysis that can test for a variety of cancers at once, rather than just one at a time.16,17

Many MCED tests are under investigation to detect cancer signals in DNA sequences, RNA sequences, DNA methylation, DNA fragmentation, protein levels, or antibodies in the blood. Currently, no MCED test is recommended in professional guidelines.16.Eventually, MCED’s use of biomarker testing as a screening tool may help find cancers at earlier stages.16,18

Infographic suggesting how monitoring minimal residual disease (MRD) could inform future treatment

MRD Monitoring

Diagnosis

Treatment

Post-treatment

ctDNA

Time from treatment

For illustrative purposes only.

Monitor minimal residual disease (MRD) to inform future treatment

Knowing the MRD status of a patient in terms of the presence or absence of a very small number of tumor cells that have survived treatment19 may help you decide whether to continue treatment to improve outcomes or de-escalate treatment to reduce toxicities.20

MRD is usually assessed using traces of circulating tumor DNA (ctDNA) in the blood. Other MRD signals have also been explored, such as circulating tumor cells (CTCs) and non-coding RNA.21 While MRD is more established in blood cancers,22,23 it is also being investigated in solid tumors, including lung,24,25 breast,26,27 ovarian,28 and prostate cancers.29

aUnder maximum benefit, 267 (68%) of those individuals would be intercepted before usual care. Applying the hazard reduction from stage at interception when compared with original stage at diagnosis, only 163 of those individuals would die within 5 years of the original diagnosis date, a 39% reduction in mortality for an absolute reduction of 104 deaths per 100,000, resulting in a relative all-cancer mortality reduction of 26%.18

CTC, circulating tumor cell; ctDNA, circulating tumor DNA; DNA, deoxyribonucleic acid; MCED, multi-cancer early detection; MRD, minimal residual disease; RNA, ribonucleic acid.

Novel Biomarkers Reveal Potential Treatment Opportunities

An increasing armamentarium of biomarkers can help support cancer diagnosis and treatment at the earliest stage possible. Novel biomarkers can help identify new patient subsets, complement established biomarkers, and provide MDTs with increasingly informed and efficient options in cancer treatment.30

The Association of Molecular Pathology (AMP) offers a wealth of resources, including webinars on evolving biomarkers.

View Association of Molecular Pathology resources
Zoomed in view of scientist hand holding petri dish

Novel Biomarkers May Have Prognostic and Predictive Value to Patients With Metastatic NSCLC

Emerging data point to STK11, KEAP1, and/or SMARCA4 as novel biomarkers that may help guide clinical management of patients with metastatic NSCLC.31 Small, retrospective, exploratory subgroup analyses in NSCLC suggest that:

Potentially Prognostic

Inactivation of these genes may negatively impact disease outcomes in patients with NSCLC32–35

  • STK11 inactivation
  • KEAP1 inactivation
  • SMARCA4 inactivation

Potentially Predictive

These genes are potentially associated with poorer response to immunotherapy regimens vs wild-type33,34,36

  • STK11 mutationsa
  • KEAP1 mutationsb
  • SMARCA4 mutation + KRAS co-mutation (36% co-occurrence, compared with KRAS mutations alone)c

This gene is potentially associated with positive response to immunotherapy regimens vs wild type32,37

  • SMARCA4 mutationc

Prevalence of STK11, KEAP1, and SMARCA4 in advanced/metastatic NSCLC38,39,d,e

GeneAverage frequency (%)fFrequency range (%)

STK11

17

16–20

KEAP1

17

16–20

SMARCA4

10

N/A

  • KRAS-mutant NSCLC represents a large and highly heterogeneous patient subgroup (~30% of NSCLC) with a poorer prognosis and a high comutation rate that can complicate treatment planning37,40–42 
  • KRAS mutations frequently co-occur with STK11, KEAP1, and/or SMARCA4 mutations32,35,38 
  • These comutated subgroups may be associated with suboptimal outcomes to IO regimens32,34–36,43,g
  • Additional investigation is needed to further characterize novel biomarkers of interest (including mutations in STK11, KEAP1, and SMARCA4) that have the potential to aid in patient selection for 1L immunotherapy regimens in patients with NSCLC
  • To help better inform treatment planning for metastatic NSCLC patients who are eligible for 1L immunotherapy, novel prognostic and predictive biomarkers are an evolving area of research.31

aBased on 2 retrospective studies of nonsquamous NSCLC patients: a pooled analysis of 32 patients from 2 trials who had an STK11 mutation and had received a single-agent PD-(L)1 inhibitor,33 and a cohort of 66 PD-L1–positive (≥1%) patients with STK11 mutations (irrespective of KRAS status) who received single-agent PD-(L)1 inhibitor therapy or combination PD-(L)1 inhibitor and CTLA-4 inhibitor therapy.36 Patient staging and previous lines of therapy were not specified in these analyses.33,36 bBased on 2 retrospective studies of NSCLC patients: a pooled analysis of 45 patients with nonsquamous NSCLC from 2 trials who had a KEAP1 mutation and had received a single-agent PD-(L)1 inhibitor,33 and an analysis of 2 cohorts of patients with lung adenocarcinoma and a KEAP1 mutation. Cohort 1, the blood-based NGS cohort, analyzed 304 patients from 2 studies who received single-agent PD-(L)1 inhibitor therapy. Cohort 2, the tissue-based NGS cohort of 343 patients derived from a cohort and 2 studies did not specify the immunotherapy regimen.34 Patient staging and previous lines of therapy were not specified in these analyses.33,34 cBased on 2 retrospective studies of NSCLC patients: an analysis of 2 separate cohorts of 77 and 18 patients with KRAS mutations with or without SMARCA4 mutations and who had received immunotherapy,37 and a cohort of 86 patients with SMARCA4 mutations across all histologies and of any stage who had received an immunotherapy regimen.32 Patient staging was not specified in the first analysis and the immunotherapy regimen and previous lines of therapy were not specified in either analysis.32,37 dThere is prevalent co-occurrence of these 3 mutations in NSCLC. A retrospective analysis of real-world data in patients with Stages IIIB, IIIC, IVA, and IVB nonsquamous NSCLC found that tumors carrying either STK11 and/or KEAP1 mutations occurred in 30% of patients (n=2276).38 In a single-institution retrospective analysis of patients with any stage of NSCLC, SMARCA4 mutations co-occurred with KEAP1 in 41% of SMARCA4-mutant tumors and with STK11 in 39% of SMARCA4-mutant tumors (n=407).32 eBased on 2 retrospective analyses of real-world data from NSCLC patients: an analysis of 2276 patients from a database with Stage IIIB, IIIC, IVA, or IVB nonsquamous NSCLC classified by 1L treatment across 5 treatment classes (STK11 and KEAP1 only),38 and an analysis of 12,934 patients from a database with advanced NSCLC (STK11, KEAP1, and SMARCA4).39 Disease stage and histology were not specified in the second analysis.39 fAverage frequencies were calculated as weighted averages; weighting was based on the total number of participants in each study. Frequency for SMARCA4 is not an average, but based on Liu et al.39 Please see additional details in footnote e. gBased on 4 retrospective analyses: a retrospective analysis of 532 patients with advanced NSCLC (stage and histology not specified) who had received at least one dose of a PD-L(1) inhibitor alone or in combination with a CTLA-4 inhibitor,43 and a retrospective subgroup analysis of 1202 patients with Stage IV metastatic nonsquamous NSCLC who had received a PD-L1 inhibitor + chemotherapy, a VEGF inhibitor + chemotherapy, or a PD-L1 inhibitor + a VEGF inhibitor + chemotherapy as 1L therapy.35 Please see footnote a for the details of reference 36, and footnote b for the details of reference 34.

1L, first-line; AMP, Association of Molecular Pathology; CTLA-4, cytotoxic T-lymphocyte-associated protein 4; KEAP1, kelch-like ECH-associated protein 1; KRAS, Kirsten rat sarcoma virus; MDT, multidisciplinary team; N/A, not applicable; NGS, next-generation sequencing; NSCLC, non-small cell lung cancer; PD-L1, programmed death-ligand 1; SMARCA4, SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4; STK11, serine/threonine kinase 11; VEGF, vascular endothelial growth factor.

Understanding of HER2 status across solid tumors and its predictive and prognostic role is evolving44,45

HER2 (ERBB2) is a known proto-oncogene first described in breast cancer.46 HER2 overexpression is a negative prognostic factor in multiple tumor types, including gastrointestinal (GI), endometrial, and ovarian.44

HER2 protein overexpression (score IHC 3+) may occur regardless of HER2 (ERBB2) amplification or HER2 (ERBB2) mutational status.47,48 Prevalence varies among tumor types but is associated with aggressive disease, poor outcomes, and increased recurrence risk.44,49,50

Prevalence of HER2 alterations across solid tumors

The prevalence of HER2 alterations varies in type of alteration and between tumor types.51

HER2 IHC 3+ (%)HER2 IHC 2+ (%)HER2 (ERBB2) amplificationa (%)HER2 (ERBB2) mutationb (%)

Breast52–59

10–20

19–49

13–23

2–4

NSCLC52,53,60–66

1–5

1–19

~1

2–4

Gastric/EGJ52,53,67–71

3–14

5–14

9–20

1–9

Biliary tract52,53,72–78

5–10

12–24

5–7

6–10

Pancreas53,56,59,77,79–81

1–7

6–9

2–24

1–3

Colorectum53,59,77,82–89

1–4

2–9

3–6

3–6

Bladder52,53,56,59,77,90–93

4–13

5–52

2–8

6–13

Endometrium53,56,59,77,94–97

3–28

14–39

4–8

2–3

Ovary52,53,56,59,77,98–101

1–5

0–24

1–2

1–3

Cervix52,53,56,59,102,103

4–11

14–18

3–7

2–5

aERBB2 (HER2) amplification is measured using ISH techniques, including FISH, CISH and SISH, or by NGS.45, 64b ERBB2 (HER2) mutations are detected through sequencing techniques, such as NGS or Sanger sequencing.63,83

HER2-positivity can enhance the metastatic potential of tumor cells104; a HER2-positive status may be a predictive factor, and HER2 testing is recommended for multiple metastatic solid tumors.105–116

Find out more about HER2 (ERBB2) mutations in mNSCLC.

Review testing guidelines
Microscopic slide showing stained cells that are positive for HER2 using immunohistochemistry (IHC)

Follow testing recommendations in solid tumors with HER2 overexpression to inform treatment options

Test for HER2 by IHC at metastatic diagnosis, to ensure that patients with a solid tumor receive personalized care.117,118

Summary of HER2 testing recommendations in guideline

Oncology specialtyTumor typeScoring criteria publishedHER2 testing recommendations in the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®)HER2 tests included in tumor-specific CAP templates for reporting of biomarker testing results123–128
HER2 overexpressionHER2 (ERBB2) amplificationHER2 (ERBB2) mutation
BreastBreastASCO-CAP Guidelines118IHC, ISH108IHCISH
GastrointestinalBiliary tractNo universal guideline119IHC, FISH, NGS109General biomarker template availablec
Gastric/EGJASCO-ASCP-CAP Guidelines120IHC, ISH, NGS110,111IHCISH or Genomic testGenomic test
PancreaticNo universal guideline119IHC, NGS (amplification)112General biomarker template availablec
ColorectalHERACLES trial scoring criteria121IHC, FISH, NGS105,106IHCISH or Genomic testGenomic test
ThoracicNSCLCNo universal guideline119Sanger sequencing, targeted PCR and NGS (mutation)113IHCGenomic testGenomic test
GenitourinaryBladderNo universal guideline119IHC114General biomarker template availablec
GynecologicEndometrialFader trial scoring criteria122IHC, FISH107IHCISH
OvarianNo universal guideline119IHC115General biomarker template availablec
CervicalNo universal guideline119IHC, FISH116General biomarker template availablec

aAssay-scoring system combinations should be validated according to the intended clinical use of the test, and the validation cohort should consist of at least 20 positive and 20 negative tissues.129  bScoring criteria at discretion of laboratory director.129  cWhere specific templates are not available, the CAP template for Reporting Results of Quantitive IHC Biomarker Testing of Specimens from Patients With Carcinoma may be used.128

ASCO-ASCP-CAP; American Society of Clinical Oncology-American Society for Clinical Pathology-College of American Pathologists; BRAF, v-raf murine sarcoma viral oncogene homolog B1; CCA, cholangiocarcinoma; CISH, chromogenic in situ hybridization; ERBB2, erb-B2 receptor tyrosine kinase 2; FISH, fluorescence in situ hybridization; GI, gastrointestinal; HER2, human epidermal growth factor receptor 2; IHC, immunohistochemistry; ISH, in situ hybridization; NCCN, National Comprehensive Cancer Network; NGS, next-generation sequencing; mNSCLC, metastatic non-small cell lung cancer; RAS, rat sarcoma; SISH, silver-enhanced in situ hybridization.

Most patients with breast cancer classified as IHC 0 have detectable levels of HER2 expression which could transform how we diagnose breast cancer.130–133

Evaluating HER2 IHC Expression Beyond Breast Cancer

ASCO-CAP and ASCO-ASCP-CAP have issued distinct guidelines for HER2 testing/scoring for breast and gastric cancers, defining distinct criteria for HER2-positivity by IHC (score IHC 3+) in the different tumor types. While circumferential membranous staining is required for an IHC score of 3+ for breast tumors, basolateral (“U”-shaped) membrane staining can be observed in IHC 3+ gastric tumors.119,121.Applying breast scoring criteria to gastric tumor specimens may lead to false-negative classification.119,121

HER2 expression extends beyond binary classification of positive or negative and may reveal biological differences130–136

HER2-negative is the most common breast cancer subtype, accounting for approximately 85% of all breast cancers.134 Despite being classified as HER2-negative, many of these tumors still carry some level of HER2 expression.135 It is estimated that approximately 60–65% of HER2-negative breast cancers are HER2-low.130,136

ASCO-ASCP-CAP, American Society of Clinical Oncology-American Society for Clinical Pathology-College of American Pathologists; HER2, human epidermal growth factor 2; IHC, immunohistochemistry.

Access educational resources, clinical cases and tools to evaluate your HER2 IHC scoring consistency in solid tumors.

Visit HER2Know.com
Microscopic slide showing stained cells that are positive for HER2 using immunohistochemistry (IHC)

HER2, human epidermal growth factor 2; IHC, immunohistochemistry.

Dark key takeaway icon

Considerations for Your Practice

Adopt cutting-edge improvements to help refine your MDT’s approach to biomarker and genetic testing and inform treatment decisions.

  • Identify the right lab system and set up for your MDT
    • Instigate laboratory training on digital pathology to improve workflow
    • Aim for timelier diagnosis with computational pathology and deep learning algorithms
  • Review screening protocols with the aim of detecting more cancers at treatable stages 
  • Monitor methods for ensuring patients are not lost to follow up post-treatment
  • Align with guidelines on the latest biomarker testing recommendations

Explore solutions to common testing challenges encountered in your workflow

Find solutions

Hear from experts on best practice in biomarker testing

Browse resources

MDT, multidisciplinary team.

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