2,114,850 Americans are projected to be diagnosed with cancer in 2026

That is approximately 5,800 new diagnoses every day.

The American Cancer Society also projects 626,140 cancer deaths in 2026.

Those numbers make the United States look like an obvious oncology expansion market.

But for a HealthTech, diagnostics, clinical AI, precision oncology, cell therapy or therapeutics company, “enter the US” is not a commercialization strategy.

It is a geographic description.

The actual question is:

Which US oncology ecosystem gives this specific product the fastest credible path from evidence to buyer to paid deployment to repeatable scale?

That is why I would not treat:

Boston = New York = Bay Area = Houston = Chicago

Each hub has a different combination of:

• academic cancer centers
• clinical trial infrastructure
• KOL access
• diagnostics and biopharma concentration
• health-system buyers
• payer complexity
• implementation partners
• investor networks
• cost of entry
• reference-account value

And that combination matters because a first US deployment is not only a contract.

It is supposed to create the evidence, relationships and implementation assets that make deployment number two easier.

Sources:
American Cancer Society, Cancer Facts & Figures 2026: https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/2026-cancer-facts-figures.html
ACS 2026 statistics release: https://pressroom.cancer.org/cancer-statistics-report-2026

Why geography matters more in oncology than a generic “US market” model suggests

The US oncology market is large, but access to oncology expertise and research is uneven.

ASCO reported that the number of hematology and medical oncologists increased from 12,267 in 2014 to 14,547 in 2024, while oncologist density relative to the population age 55+ fell from 15.9 to 14.9 per 100,000.

ASCO also found that around 11% of adults age 55+ lived in the 55% of US counties without a practicing oncologist.

That matters commercially.

Oncology innovation is not distributed evenly across the country.

The strongest hubs concentrate:

• oncologists
• NCI-designated cancer centers
• specialist trials
• molecular diagnostics
• pharma partnerships
• digital oncology programs
• precision medicine infrastructure
• commercialization talent

For a founder, that concentration can accelerate evidence and reference creation.

For an investor, it can also create a false positive.

A startup can win one prestigious pilot inside a sophisticated cancer center and still fail to prove that its sales motion works outside that ecosystem.

Source: ASCO State of Cancer Care in America / oncology workforce analysis:
https://www.asco.org/research-data/state-cancer-care-america

The commercial signal is not hypothetical

Tempus reported $382.5M of Q2 2026 revenue, up 22% year over year, while its oncology volume increased 31% year over year.

Its Data and Applications business generated $93.2M, up 28%, and the company reported signing approximately $200M in new Data and Applications licenses during the quarter.

That does not prove that every oncology AI or diagnostics company will scale.

It does show that significant commercial demand exists when a company combines:

clinical workflow + data + diagnostics + buyer relevance + reimbursement + enterprise distribution.

That is a much more useful commercialization signal than simply saying “oncology is growing.”

Source: Tempus Q2 2026 results:
https://investors.tempus.com/news-releases/news-release-details/tempus-reports-second-quarter-2026-results

My US Oncology Market Entry Framework

I would score a prospective first hub through five commercial gates.

01. BUYER DENSITY

Do enough relevant economic buyers exist within a manageable geography?

A city can have extraordinary oncology science but still be a weak first market if your actual buyer is scarce.

Depending on the product, your buyer might be:

• health-system oncology leadership
• pathology
• radiology
• molecular diagnostics
• CIO / digital
• CMIO
• clinical operations
• pharmacy
• research
• biopharma
• revenue cycle
• payer
• employer oncology benefits

The logo is not the buyer.

The department and budget owner matter.

02. KOL + EVIDENCE ACCESS

Can the market generate the evidence your second customer will believe?

The strongest first site is not always the institution with the largest patient volume.

It may be the institution that can generate:

• clinical validation
• health-economic evidence
• workflow evidence
• peer-reviewed data
• a recognized KOL
• a referenceable case study
• trial infrastructure
• payer-relevant outcomes

That distinction is critical.

A pilot that creates no portable proof can consume cash without creating commercial leverage.

03. PAYER + REIMBURSEMENT FIT

Who ultimately pays?

Oncology products can sit across very different reimbursement structures:

• hospital budget
• professional reimbursement
• laboratory reimbursement
• medical benefit
• pharmacy benefit
• value-based care
• clinical-trial budget
• biopharma services
• employer / navigation benefit
• direct enterprise contract

A startup can achieve clinical enthusiasm and still fail commercially because the evidence was created for the wrong economic stakeholder.

04. PILOT TO CONTRACT

Does the first engagement have a defined conversion mechanism?

Before a pilot starts, I would want answers to:

• What is the success KPI?
• Who signs the full contract?
• Which budget funds scale?
• What happens after the pilot?
• Does the deployment expand by site, service line, cancer type or user?
• Is security / integration repeated?
• Can the reference be used externally?
• What is the renewal trigger?

A pilot without a conversion mechanism is often research, not GTM.

05. COST + INTEGRATION BURDEN

How much runway does this city require before commercial proof?

Founders often compare markets through theoretical TAM.

I would compare:

capital required to create a repeatable reference account

That includes:

• travel
• local hiring
• business development
• clinical support
• integration
• evidence generation
• regulatory work
• legal / contracting
• procurement
• pilot implementation

The cheapest city is not necessarily the best market.

The right question is:

Which hub creates the most reusable commercial proof per dollar of runway?

The five oncology hubs

The hub descriptions below are a commercialization lens, not an official ranking.

The National Cancer Institute confirms that these regions contain major NCI-designated cancer centers, including Dana-Farber/Harvard in Boston, multiple comprehensive cancer centers in New York, UCSF and Stanford in Northern California, MD Anderson and Baylor in Houston, and Northwestern and the University of Chicago in Chicago.

Source: NCI Cancer Center directory:
https://www.cancer.gov/research/infrastructure/cancer-centers/find

1. Boston / Cambridge

Commercial wedge: precision oncology, translational science and therapeutics

Boston is especially attractive when the product needs:

• deep translational science
• academic KOLs
• genomics
• precision oncology
• biopharma partnership
• early clinical validation
• venture connectivity

Anchor institutions and strategic ecosystem

• Dana-Farber Cancer Institute
• Mass General Brigham
• Harvard Medical School
• Broad Institute
• Beth Israel Lahey Health

Dana-Farber/Harvard Cancer Center is an NCI-designated Comprehensive Cancer Center.

Emerging / specialist company watchlist

• Predicta Biosciences
• Nested Therapeutics
• Harmonia Therapeutics
• Marendis Therapeutics
• Neoclease

Predicta is building a molecular insights platform for blood cancer and is based in Cambridge.

Nested Therapeutics is also Cambridge-based and is developing precision oncology medicines.

Important diligence note: Neoclease is relevant to the broader precision-biotech ecosystem, but its currently disclosed lead editor targets LRRK2 in Parkinson’s disease. I would therefore treat it as an adjacent gene-editing signal, not as a current pure-play oncology company.

Best route

Partner-led entry often makes more sense than building a large local sales organization first.

Look for:

KOL → validation partner → translational proof → strategic / buyer conversation

Founder mistake to avoid

Do not confuse scientific validation with a repeatable buying motion.

Boston can make a technology look credible very quickly.

That does not automatically make it commercially repeatable.

Investor question

Can the company convert Boston-grade evidence into contracts outside Boston?

2. New York

Commercial wedge: clinical scale, diagnostics, pathology, oncology workflow and dense enterprise access

New York combines large health systems, sophisticated cancer centers, pathology infrastructure and a dense enterprise ecosystem.

NCI-designated centers in New York City include Memorial Sloan Kettering, Columbia’s Herbert Irving Comprehensive Cancer Center, NYU Langone’s Perlmutter Cancer Center, Montefiore Einstein and Mount Sinai Tisch Cancer Center.

Anchor institutions and strategic ecosystem

• Memorial Sloan Kettering Cancer Center
• NYU Langone Health
• Columbia University Irving Medical Center
• Weill Cornell Medicine
• Montefiore

Emerging / specialist company watchlist

• Triomics
• Paige
• PreciseDx
• OncoPrecision
• Tracer Biotechnologies

Triomics announced an oncology-specific AI trial-matching deployment across Mount Sinai in 2026.

Paige remains a major pathology-AI player with New York operations.

PreciseDx is developing AI-enabled morphology-based oncology diagnostics.

OncoPrecision is developing ADC and bispecific programs from New York.

Tracer is developing ctDNA monitoring technology and has announced a multi-year collaboration with AstraZeneca.

Best route

Hybrid entry

Use strategic clinical partners and KOLs, but build the commercial hypothesis around a defined buyer and budget owner.

Founder mistake to avoid

Do not try to “sell New York.”

The health systems are too complex for a generic enterprise pitch.

Map:

institution → cancer program → stakeholder → economic owner → procurement path

Investor question

Does the company have a repeatable account model, or is every New York institution effectively a new market?

3. Bay Area

Commercial wedge: precision diagnostics, AI, biotech partnerships and early-adopter innovation

The Bay Area combines NCI-designated cancer centers with biotech, venture and AI density.

NCI lists both the UCSF Helen Diller Family Comprehensive Cancer Center and Stanford Cancer Institute as Comprehensive Cancer Centers.

Anchor institutions and strategic ecosystem

• UCSF Health
• Stanford Medicine
• Genentech
• GRAIL
• Guardant Health

Emerging / specialist company watchlist

• Clarified Precision Medicine
• Cartography Biosciences
• Veracyte
• Oncobox
• ARNA Genomics US

Clarified Precision Medicine is headquartered in San Francisco and focuses on interpretation of molecular testing for precision oncology.

Cartography Biosciences is based in South San Francisco and is building precision oncology therapeutics from single-cell data.

Veracyte is a major diagnostics company in the region.

Oncobox is a precision-oncology platform worth monitoring for its molecular treatment-selection approach.

ARNA Genomics US has a California office and works in molecular / genomics applications.

Best route

Partner-led or strategic ecosystem entry

Especially useful when the company needs:

• innovation partners
• biotech collaborations
• data partnerships
• early adopter health systems
• venture introductions

Founder mistake to avoid

High innovation density can create lots of conversations without creating revenue.

Measure:

paid conversion, implementation time and repeatable deployment, not meeting volume.

Investor question

Does the company have differentiation strong enough to survive an unusually competitive innovation environment?

4. Houston

Commercial wedge: clinical oncology, cell therapy, translational research and direct clinical partnership

Houston is different.

Its advantage is not simply startup density.

It is the concentration of major cancer institutions around the Texas Medical Center and the presence of NCI-designated MD Anderson and Baylor’s Dan L Duncan Comprehensive Cancer Center.

Anchor institutions and strategic ecosystem

• MD Anderson Cancer Center
• Baylor College of Medicine
• Texas Children’s Hospital
• Houston Methodist
• AstraZeneca

Emerging / specialist company watchlist

• Tvardi Therapeutics
• Kiromic Biopharma
• NKILT Therapeutics
• Stellanova Therapeutics
• EMPIRI

Tvardi is Houston-area based and has a liver-cancer program in its clinical portfolio.

NKILT is developing off-the-shelf engineered NK-cell therapy.

EMPIRI is Houston-based and is commercializing an ex vivo tumor-tissue platform. In 2026, it received a roughly $1.25M NSF SBIR Phase II award for development of a cancer diagnostic instrument.

Best route

For the right clinical product, Houston can support a more direct clinical-partnership route.

That can be particularly attractive where the commercial motion depends on:

• tumor tissue
• cell therapy
• oncology trials
• functional testing
• clinical workflow
• hospital implementation

Founder mistake to avoid

Do not assume a major cancer center partnership automatically opens the broader US market.

Design the first deployment so the outputs are portable.

Investor question

Does the Houston reference create evidence that community oncology, other academic centers or biopharma customers will buy?

5. Chicago

Commercial wedge: oncology data, precision-care infrastructure and integrated enterprise deployment

Chicago combines major health systems, academic cancer centers, pharma and a growing oncology data / precision-care ecosystem.

NCI lists both Northwestern’s Robert H. Lurie Comprehensive Cancer Center and the University of Chicago Comprehensive Cancer Center.

Anchor institutions and strategic ecosystem

• Northwestern Medicine
• Rush
• UChicago Medicine
• AbbVie
• Takeda

Emerging / specialist company watchlist

• Tempus AI
• Nucleai
• CancerIQ
• NUAgo Therapeutics
• ExoMira Medicine

Tempus is headquartered in Chicago and provides one of the strongest current signals for commercial oncology data and diagnostics demand.

CancerIQ is Chicago-based and says its platform is trusted by 275+ clinics nationwide.

Nucleai works in AI-powered spatial biomarkers and computational pathology.

NUAgo is advancing RNAi-based oncology therapeutics.

ExoMira Medicine describes itself as a Chicago-based Northwestern spinout developing cancer immunotherapies.

Best route

Hybrid

Chicago can work well for products that need both:

• sophisticated clinical proof
• an enterprise / data commercialization story

Founder mistake to avoid

Do not pitch AI or data as the product.

Tie it to:

workflow, revenue, precision-care decisions, patient identification, trial acceleration or measurable clinical value.

Investor question

Is the data layer monetizable independently, or only valuable because it supports another product?

One map, five different market-entry motions

This table is an editorial GTM lens, not a formal ranking or procurement forecast.

Product type should change the hub decision

There is no universal “best oncology city.”

I would alter the weighting by product.

Precision oncology / therapeutics

Increase the weighting on:

KOL access + translational science + trial infrastructure

Boston, Houston and the Bay Area may deserve early consideration.

Oncology diagnostics

Increase:

sample access + pathology + reimbursement + clinical implementation

Boston, New York, Bay Area and Chicago can each offer different advantages.

Clinical AI / workflow

Increase:

buyer density + integration + measurable hospital ROI

New York, Chicago and the Bay Area may look more attractive depending on workflow ownership.

Cell therapy

Increase:

specialist clinical infrastructure + trial operations + manufacturing / partner ecosystem

Houston and Boston can become more relevant.

Oncology data / RWE

Increase:

data access + biopharma demand + enterprise licensing + research network

Chicago, New York and Boston may warrant higher weighting.

That is why I do not like generic “top oncology city” rankings.

The correct answer changes when the product changes.

The ROI question: how expensive is a wrong first hub?

The accompanying calculator converts the market-entry decision into runway economics.

Consider an illustrative company with:

Monthly US commercialization burn: $60,000
Wrong-market delay risk: 6 months
Pilot + integration cost: $100,000
Expected first-year contract value: $250,000
Qualified win probability: 30%
Gross margin: 75%

Runway exposed to delay

$60,000 × 6 = $360,000

Add the pilot / integration cost:

$360,000 + $100,000 = $460,000

$460K of capital is exposed before repeatable scale

This is an illustrative company scenario, not a US oncology benchmark.

Now compare that with probability-weighted deal economics

Expected first-year contract:

$250,000

Qualified win probability:

30%

Probability-weighted revenue:

$250,000 × 30% = $75,000

Apply 75% gross margin:

$75,000 × 75% = $56,250

Probability-weighted first-year gross profit = $56,250

Now compare market-entry exposure:

$460,000 ÷ $56,250 ≈ 8.2×

That does not mean the company should avoid the US.

It means:

a bad market-entry sequence can consume far more capital than the first account economically justifies.

The ROI of saving four months

Suppose better hub selection, buyer mapping and evidence planning reduce the time to a credible commercial decision by four months.

4 × $60,000

=

$240,000 of runway preserved

That is the kind of market-intelligence ROI I care about.

Not:

“We found 500 oncology contacts.”

But:

“We avoided six low-fit accounts and reached the right evidence / buyer route four months earlier.”

The second ROI layer: account concentration

Imagine you research 25 oncology buyers / partners.

After scoring them on:

• product fit
• evidence requirement
• reimbursement
• integration
• buying authority
• pilot-to-contract potential
• reference value

only 32% are genuinely attractive.

That leaves:

8 priority accounts

Now assume warm senior-level access exists at only 25% of those accounts.

That gives:

2 warm priority accounts

The commercial problem is no longer:

“We need more US oncology leads.”

It becomes:

“We have six high-fit accounts where the buyer relationship and access route are still missing.”

That is a much more precise GTM problem.

What founders should calculate before choosing a city

I would model six variables.

Buyer Fit

Can you identify the actual economic buyer?

Evidence Fit

Can this hub produce evidence the next buyer values?

Reimbursement Fit

Can you explain how money reaches the product?

Pilot-to-Paid Fit

Is there a contractual scale path before the pilot starts?

Integration Burden

How much technology, data and workflow work is required?

Expansion Value

Will the first reference reduce friction for account two?

The calculator weights all six.

Then it layers the company’s own readiness on top.

What investors should diligence

I would not use pilot count as the headline metric.

Instead, test this sequence:

PILOT → PAID ROLLOUT → MULTI-SITE → RENEWAL → EXPANSION

Then ask:

Evidence portability

Can evidence from one institution support the next sale?

Integration reuse

Does deployment two require less technical work?

Buyer repeatability

Is the same economic buyer involved across accounts?

Reimbursement clarity

Is the product paid through a durable mechanism?

Reference value

Does the first hub strengthen market two?

Geographic concentration risk

Is traction dependent on one unusually innovation-friendly institution?

Sales efficiency

Does each customer make the next one cheaper to win?

For me, that last question is one of the strongest commercialization tests.

What hospital and oncology executives should ask vendors

This map is also useful from the buyer side.

I would ask:

• What exact oncology workflow changes?
• Who uses the product?
• Who owns implementation?
• Which system must integrate?
• What evidence supports clinical value?
• What evidence supports economic value?
• How much clinician time changes?
• Does it create another screen or remove one?
• Who supports the product after the pilot?
• What is the full-cost implementation?
• Which KPI determines renewal?
• What happens if the pilot works?

That makes vendor evaluation more defensible.

How I would sequence US oncology entry

My practical framework is:

HUB → BUYER → KOL → EVIDENCE → PAYMENT → PILOT → REFERENCE → REPEAT

Not:

CITY → CONFERENCE → MEETINGS → HOPE

The difference is sequencing.

Step 1: choose the evidence you need

Before choosing the city, define what market-entry proof is missing.

Examples:

Clinical AI: workflow time, sensitivity, specificity, adoption, integration, financial impact
Diagnostics: analytical / clinical validity, actionability, reimbursement, sample workflow
Therapeutics: KOL, translational evidence, trials, pharma partnership
Data platform: data access, life-science buyer value, licensing, reproducibility
Patient navigation: completion rates, access, retention, treatment adherence

Then choose the hub capable of generating that proof.

Step 2: choose the buyer before building the pipeline

Do not start with “oncology hospitals.”

Start with:

What job is being funded?

Then map the budget owner.

A radiology AI company and a molecular diagnostics platform should not receive the same account list.

Step 3: design the first site to become a commercial asset

The first site should ideally generate:

• measurable results
• an implementation template
• security / integration documentation
• stakeholder references
• workflow proof
• buyer ROI
• public evidence where possible
• expansion rights or a route to another site

If the pilot generates none of these, its commercial ROI may be low even if the clinical result is positive.

Step 4: price the cost of waiting

Every month spent on a low-fit geography has a cost.

Use:

Monthly US GTM burn × avoidable months = runway at risk

Then add:

pilot + integration + local overhead

That number often changes the market-entry conversation dramatically.

Step 5: concentrate the buyer universe

This is where I can help.

I do not think most oncology founders need another list of 500 US healthcare organizations.

They need to know:

Which 25 buyers / partners deserve attention now, and which 15 people inside them can actually move the deal?

That is the gap between market research and revenue execution.

How I can help: HealthTech Buyer Pipeline Sprint

The HealthTech Buyer Pipeline Sprint is designed to turn this market-entry analysis into a concentrated commercial pipeline.

Instead of generic lead generation, I map:

25 priority buyers / partners + 15 relevant decision-makers

against the company’s actual:

• oncology category
• product stage
• evidence
• reimbursement path
• integration burden
• target workflow
• budget owner
• pilot model
• geographic strategy
• reference-account requirement

The objective is not more contacts.

It is:

• fewer low-fit conversations
• stronger account prioritization
• better buyer ownership
• less wasted founder time
• clearer outreach hypotheses
• faster learning around real procurement barriers

Product:
https://growthvybz.com/products/healthtech-buyer-pipeline-sprint-25-buyers-15-decision-makers

A buyer pipeline should look different by category

If you are an oncology diagnostics company

The 25-account universe might emphasize:

• molecular pathology
• comprehensive cancer centers
• cancer networks
• precision-medicine programs
• diagnostics partners
• payers
• pharma trial partners

If you are clinical AI

I would weight:

• health-system oncology operations
• specialty service lines
• CMIO / CIO stakeholders
• workflow owners
• informatics
• integration partners

If you are therapeutics / biotech

I would weight:

• KOLs
• trial sites
• translational partners
• biopharma
• cancer centers
• investors
• strategic BD

If you are oncology data / RWE

I would weight:

• biopharma data buyers
• cancer centers
• research networks
• diagnostics platforms
• informatics leaders
• trial operators

The pipeline should reflect the product.

Not the keyword “oncology.”

The market-entry equation

My commercial equation for a first US oncology hub is:

ENTRY VALUE =

Buyer density
× Evidence portability
× Payment clarity
× Pilot conversion probability
× Reference value

divided by:

Sales-cycle + integration + local cost friction

That is why the largest city is not necessarily the best first market.

And the most prestigious cancer center is not necessarily the best first customer.

Final takeaway

The United States is projected to see 2.11M+ new cancer diagnoses in 2026.

Commercial demand is real.

Tempus’s Q2 2026 results show that oncology diagnostics and data can scale rapidly when product, evidence and commercial infrastructure align.

But founders should resist one dangerous simplification:

“US oncology” is not one market.

Boston, New York, the Bay Area, Houston and Chicago are different commercialization systems.

The best first hub is the one that can turn your current weakness into reusable commercial proof.

That means:

HUB → BUYER → EVIDENCE → PAYMENT → PILOT → REFERENCE → SCALE

For founders, that protects runway.

For executives, it makes market-entry investment more defensible.

For investors, it separates “US interest” from a genuinely repeatable US commercialization engine.

And that is the real objective.

Not entering America.

Building a route through America that gets cheaper and more repeatable after every win.