Second primary cancers following hematologic malignancies: Epidemiology, pathobiology and clinical management.

Introduction

Hematologic malignancies, which encompass leukemia, lymphoma, and multiple myeloma (MM), constitute a heterogeneous group of disorders originating from the blood and hematopoietic system. 1–3 Recent advances in antineoplastic therapies and earlier detection methods have significantly improved long-term survival rates among patients with these malignancies. However, an increasing number of survivors are developing second primary cancers (SPCs), defined as newly diagnosed, histologically distinct malignant tumors identified either concurrently (within 6 months) or subsequently (after 6 months) to the initial hematologic malignancy, excluding cases of metastatic disease and local recurrence. 4–6 The emergence of SPCs is influenced by a complex interplay of germline genetic susceptibility, therapy-induced cellular damage, environmental exposures, and remodeling of the tumor microenvironment. Notably, the risk of developing SPCs appears to be higher in survivors of hematologic malignancies compared to those with solid tumors. Research on SPCs following hematologic malignancies remains fragmented, lacking standardized diagnostic criteria and consensus-based management strategies in clinical practice. This narrative review systematically synthesizes the current evidence on the epidemiology, pathogenic mechanisms, and clinical management of SPCs after hematologic malignancies, aiming to provide a comprehensive reference for clinical practice and future research.

Epidemiology: a rising tide after the storm

Survivors of hematologic malignancies exhibit a significantly increased risk of SPCs compared to the general population, with standardized incidence ratios (SIRs) ranging from 1.27 to 2.60, indicating a 10–14% heightened incidence risk ( Table 1 ). 4 , 7 , 8 Population-based studies primarily provide broad risk estimates and incidence trends, whereas treatment-based cohorts enable a more precise evaluation of therapy-related carcinogenesis and dose–response associations between modalities such as radiotherapy, hematopoietic stem cell transplantation (HSCT), and chimeric antigen receptor T-cell (CAR-T) therapy. Integrating both perspectives is essential for comprehensive risk modeling. The extent of SPC risk is influenced by several factors, including disease subtype, age at diagnosis, and treatment era. Among hematologic malignancies, survivors of childhood non-Hodgkin lymphoma (NHL), mycosis fungoides (MF), and Hodgkin lymphoma (HL) represent the highest-risk groups. 9–11 While those with chronic lymphocytic leukemia (CLL) and chronic myeloid leukemia (CML) face a comparatively lower risk. 12–14 Notably, pediatric NHL survivors have reported an SIR of 19.80 (95% CI, 14.50–26.50) for any SPC when compared to age-matched peers.15 The phenotypes of SPCs vary according to age and treatment modalities. The most prevalent SPCs include therapy-related myeloid neoplasms (t-MN) and solid tumors affecting the thyroid, breast, and skin. 15 , 16 Pediatric survivors demonstrate a disproportionately high burden of SPCs compared to adults, primarily due to the increased sensitivity of developing hematopoietic and somatic tissues to cytotoxic therapies, as well as extended survival periods that allow for latent neoplastic progression. 17 Furthermore, the spectrum of SPCs has evolved in the contemporary treatment era, characterized by the introduction of CAR-T therapy and molecularly targeted agents. This evolution is evidenced by a decline in the incidence of t-MN, alongside a relative increase in solid tumors associated with chronic immune dysregulation. 18–20 Table 1. Incidence of SPCs in patients with hematological malignancies. Cancer type Registry Study period Patients (n) SIR (95% CI) PMID Multiple Myeloma SEER-9 (USA) 1973–2008 2021 1.07 (0.97–1.18) 25192415 11 Multiple Myeloma Swedish Cancer Registry 1958–1996 8656 2.19 (1.74–2.71) 11592772 15 Mycosis Fungoides SEER-18 (USA) 2000–2015 6742 10.15 (9.29–11.07) 31374302 10 Childhood NHL BFM Registry (Germany) 1981–2010 3590 19.80 (14.50–26.50) 32299903 17 Hodgkin Lymphoma SEER (USA) 2000–2020 36497 3.76 (2.67–5.30) 40406264 16 Hodgkin Lymphoma Netherlands 1965–2000 3905 4.60 (4.30–4.90) 26699166 8 Chronic Myeloid Leukemia SEER (USA) 2002–2014 9200 1.30 (1.20–1.40) 29456888 14 Chronic Lymphocytic Leukemia SEER (USA) 1973–2015 38754 1.20 (1.17–1.23) 31570695 13 Chronic Lymphocytic Leukemia Netherlands Cancer Registry 1989–2019 24815 1.63 (1.59–1.68) 36635262 12 Note: All SIRs were age- and sex-adjusted to the general population unless otherwise specified. SIR = standardized incidence ratio; CI = confidence interval; NHL = non-Hodgkin lymphoma.

High-risk populations for SPCs following hematologic neoplasms include survivors of pediatric NHL, MF, and HL. 8 , 15 , 17 In these cohorts, t-MN is more prevalent in children, while solid malignancies, such as lung, breast, and skin cancers, are more common among adults who have survived HL and MF. 7 , 8 , 17 Key modifiers of SPCs risk include cumulative radiotherapy dose, exposure to alkylating agents, age at initial treatment, and therapy-induced long-term immune dysfunction.

The roots of risk: from aging to immunosuppression and inflammation

The development of SPCs following hematologic malignancies arises from multifactorial interactions between host susceptibility and treatment- or disease-associated exposures. These factors converge to create a biological milieu conducive to malignant transformation. Based on current evidence, the principal contributors to SPCs risk can be categorized into four domains: cellular senescence associated with aging, metabolic dysregulation, oncogenic viral infections, and immune dysfunction accompanied by chronic inflammation ( Figure 1 ). The relative influence of each mechanism varies across patient subgroups and treatment regimens, highlighting the complexity of SPCs pathogenesis. Figure 1. The “soil and seed” model of SPCs risk: aging, obesity, viral infection, and immune dysregulation jointly shape a pro-oncogenic microenvironment that predisposes to the development of second primary cancers. (A) Aging induces telomere shortening and impaired DNA repair capacity in hematopoietic stem cells (HSCs), contributing to genomic instability. (B) Obesity triggers adipocyte secretion of IL-6/TNF-α, which activates the NF-κB pathway and drives chronic inflammation. (C) Oncogenic viruses (EBV, HPV, HBV) integrate into the host genome, inducing TP53 mutations or RAS pathway activation, and ultimately leading to cellular malignant transformation. (D) Immunosuppression and chronic inflammation cause ROS accumulation, which impairs DNA repair function, exhausts CD8+ T cells, and thus abrogates immune surveillance. The diagram illustrates factors contributing to the risk of second primary cancers (SPCs). Section A, labeled 'Aging', shows a human figure, hematopoietic stem cell, differentiation process and telomere shortening. Section B, 'Obesity', depicts adipocytes secreting IL-6 and TNF-alpha, leading to inflammation. Section C, 'Virus', includes icons for EBV, HBV, HPV and HIV, with viral integration into an affected cell. Section D, 'Immunosuppression and inflammation', features a shield icon, TGF-beta, IL-10 and ROS. The central image shows affected cells, with a label 'SPCs' at the bottom. The diagram highlights how these factors create a pro-oncogenic environment, increasing SPCs risk. Diagram showing SPCs risk factors: aging, obesity, virus, immunosuppression and inflammation.

Aging

Chronological aging is a well-established, non-modifiable risk factor for SPCs in both hematologic and solid tumors, exerting a particularly pronounced effect on survivors of hematologic malignancies whose hematopoietic and immune systems are already compromised. 21–23 Aging impairs genomic integrity and disrupts immune homeostasis synergistically. 24 Key hallmarks include functional defects in hematopoietic stem cells (HSCs), such as clonal expansion with diminished self-renewal capacity, myeloid lineage bias, telomere attrition, and aberrant epigenetic modifications. 21–23 , 25 Single-cell sequencing of HSCs from acute myeloid leukemia (AML) patients has revealed age-related epigenetic reprogramming, which downregulates essential differentiation genes and enriches a preleukemic HSC reservoir predisposed to malignant transformation. 23 , 26 This phenomenon correlates with higher rates of myeloid SPCs in older adults. 5 , 23 , 27 Concurrently, immunosenescence undermines antitumor surveillance, allowing incipient malignant clones to evade immune detection. 27 , 28

Obesity and metabolic disorders

Obesity and metabolic dysregulation are closely associated with an increased risk of SPCs among survivors of hematologic neoplasms, mediated through hormonal, inflammatory, and immunological pathways. 29 , 30 A large prospective cohort study demonstrated that each 5 kg/m 2 increment in body mass index (BMI) at the time of cancer diagnosis was linked to a 13% increase in SPCs incidence. 30 Adipocyte hypertrophy induces local hypoxia, which promotes macrophage infiltration and creates a chronic, low-grade inflammatory state characterized by elevated levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α). These cytokines contribute to DNA damage, proliferative signaling, and angiogenesis. 30–32 Preclinical models suggest that this inflammatory microenvironment upregulates immune checkpoint ligands, such as programmed death-ligand 1 (PD-L1), leading to CD8+ cytotoxic T-lymphocyte exhaustion and impaired immunoediting, thereby facilitating tumor cell expansion. 33–35

Viral infections

Oncogenic viruses are recognized as common risk factors for SPCs in both hematologic and solid malignancies, particularly affecting individuals with pre-existing immune dysfunction. 36 Mendelian randomization studies have indicated that patients with oropharyngeal carcinoma, likely associated with human papillomavirus (HPV) infection, have an 18% increased risk of developing NHL. 37 Pathogens such as Helicobacter pylori, hepatitis B virus (HBV), hepatitis C virus (HCV), Epstein–Barr virus (EBV), HPV, and human immunodeficiency virus (HIV) are well-established etiological agents for gastric cancer, hepatocellular carcinoma, and hematologic malignancies, including diffuse large B-cell lymphoma (DLBCL), marginal zone lymphoma, and Burkitt lymphoma. 36 , 38 , 39 This underscores the shared viral oncogenesis that contributes to both primary and second cancers.

Immunosuppression and inflammation

Persistent immunosuppression and chronic inflammation are critical factors in the pathogenesis of SPCs, as they compromise the body’s natural antitumor defenses. Immune dysregulation is intrinsic to hematologic malignancies and may be exacerbated by therapeutic interventions, resulting in enduring effects that increase the risk of SPCs. 33 , 40 , 41 Survivors of DLBCL exhibit a 17.6-fold higher incidence of infections, autoimmune disorders, and immune deficiencies compared to survivors of other cancers. Elevated baseline CD8+ T-cell counts have been linked to a lower incidence of SPCs. 42 , 43 Within the tumor microenvironment, immunosuppression is mediated by transforming growth factor-β (TGF-β) and interleukin-10 (IL-10), which inhibit effector immune responses and promote the survival of malignant cells. Oxidative stress leads to the generation of reactive oxygen species (ROS) and pro-inflammatory cytokines, such as TNF-α and IL-6, which result in DNA repair defects and accelerated telomere shortening, thereby contributing to genomic instability. 33 , 40 Preclinical studies indicate that HSCs with mutations in DNMT3A , in a preleukemic state, can acquire secondary oncogenic mutations – such as FLT3 , NPM1 , and IDH1 –in response to inflammatory stimuli, thereby driving malignant transformation. 35 , 44 Collectively, these findings underscore the crucial role of impaired immune surveillance and chronic inflammation in the development of aggressive SPCs among survivors of hematologic malignancies.

Mechanisms underlying SPCs pathogenesis in hematologic malignancy survivors

The pathogenesis of SPCs following hematologic malignancies is a dynamic and multistage process driven by the interplay of germline susceptibility, therapy-induced genotoxicity, remodeling of the tumor microenvironment (TME), and effects mediated by circulating cell-free DNA (cfDNA) ( Figure 2 ). Figure 2. Mechanisms underlying SPCs pathogenesis in hematologic malignancy survivors. (A) Genetic predisposition: Germline variants in TP53 , CHEK2 , BRCA1 , DDX41 , and low-penetrance SNPs establish a foundational risk context by abrogating DNA damage repair, cell-cycle control, and apoptosis pathways. Aberrant activation of the RAS signaling cascade further facilitates cross-lineage carcinogenesis. (B) Therapy-related factors: Radiotherapy, chemotherapy, and CAR-T cell therapy induce collateral genotoxic damage. Off-target radiation and cytotoxic agents cause DNA single-strand breaks and cellular senescence, while concurrently activating cancer-associated fibroblasts (CAFs) that remodel the bone marrow niche through proinflammatory cytokine secretion and metabolic reprogramming. (C) Tumor microenvironment remodeling: the therapy-altered niche and damaged stromal cells, secretes various factors such as TGF-β1, TNF-α and IL-6. These factors further promote the survival and clonal dominance of selected mutant hematopoietic stem and progenitor cells (HSPCs), thereby establishing a self-reinforcing pro-oncogenic loop. (D) cfDNA: Oncogenic cfDNA released from the first primary cancers can be internalized by recipient cells, potentially disrupting DNA damage response pathways and promoting malignant transformation at distant sites. Section A shows genomic changes with germline variants in TP53, CHEK2, BRCA1, DDX41 and SNPs, leading to aberrant RAS signaling activation. Section B depicts therapy-related factors like radiotherapy, chemotherapy and CAR-T cell therapy causing DNA single-strand breaks and activating CAFs. Section C illustrates tumor microenvironment remodeling with factors like TGF-β1, TNF-α and IL-6 promoting SPCs. Section D shows oncogenic cfDNA from first primary cancers being internalized by recipient cells, potentially disrupting DNA damage response pathways. Diagram of SPCs pathogenesis in hematologic malignancy survivors with genetic, therapy, microenvironment and cfDNA factors.

Genetic predisposition

Germline variants establish a foundational risk context for the development of SPCs. Singhal et al. reported that 19% of patients with lymphoid malignancies and concomitant primary cancers harbor pathogenic germline mutations, most frequently in CHEK2 , BRCA1 , DDX41 , and TP53 . 45–47 Loss of TP53 function abrogates critical tumor-suppressive pathways, including DNA damage repair, cell-cycle control, and apoptosis, thereby promoting the survival of genomically damaged clones. 48 , 49 In mediastinal non-seminomatous germ cell tumors co-occurring with hematologic neoplasms, TP53 mutations are found in up to 91% of cases, often concurrent with RAS pathway activation, which facilitates cross-lineage carcinogenesis. 50 Genome-wide association studies (GWAS) have implicated low-penetrance single-nucleotide polymorphisms (SNPs) (e.g., rs191064896, rs535484207, rs139586367) in polygenic susceptibility to SPCs among survivors of hematologic malignancies. 51 , 52 However, this hypothesis is constrained by heterogeneity in study populations and genotyping methods, necessitating further validation through large-sample, multicenter cohort studies.

Treatment-related factors

Advancements in chemotherapy, HSCT, immunotherapy, and targeted agents have significantly improved patient outcomes; however, they also induce collateral damage that increases the risk of SPCs. 53 , 54 For instance, radiotherapy elevates the risk of secondary lung cancer in patients with HL by a factor of 8.70 (95% CI: 7.90–9.60). Additionally, alkylating agents, such as melphalan, are implicated in approximately 89% of therapy-related acute myeloid leukemia (t-AML) cases among patients with multiple myeloma. 8

Radiotherapy: inducing genomic instability and immune evasion

Radiotherapy elevates the risk of SPCs through mechanisms including direct DNA damage, induction of cellular senescence, and systemic immunosuppression ( Figure 3 ). 55–57 Off-target ionizing radiation leads to the formation of single-strand breaks (SSBs) and depletes intracellular NAD+ pools, thereby impairing the PARP1 -mediated repair of these SSBs. 58 The accumulation of unrepaired lesions drives cells into a senescent state characterized by G0/G1 arrest, upregulation of p16 and p21 , increased β-galactosidase activity, and the development of a secretory phenotype. Senescent cells may subsequently escape growth arrest via a process known as Post-Senescence Neoplastic Escape (PSNE), exhibiting matrix metalloproteinase (MMP) activity and invasive behavior. 59–62 During PSNE, previously senescent cells can reacquire proliferative capacity, accompanied by genomic instability, epigenetic alterations, and activation of oncogenic signaling pathways. 56–59 These transformed cells may contribute to malignant transformation in surrounding tissues, thereby potentially increasing the risk of SPC development following radiotherapy. Figure 3. Schematic diagram of the mechanism of SPCs induced by radiotherapy and chemotherapy. Illustration: a multi-step carcinogenic process involving: (1) DNA damage (e.g., single-strand breaks in normal cells); (2) accumulation of senescent cells (characterized by p16 / p21 upregulation and SASP, with potential for post-senescence neoplastic escape); (3) immunosuppression (e.g., lymphopenia, M2 macrophage polarization, impaired immune surveillance); (4) tumor microenvironment remodeling (e.g., CAF activation, pro-inflammatory cytokine secretion, lactate and metabolite release); ultimately leading to SPCs development. The input legible and properly understood: yes. Radiotherapy sequence, top to bottom: Radiotherapy icon → DNA single-strand breaks → a cell-cycle diagram labeled G subscript 0 phase (resting), G subscript 1, S, G subscript 2 and M, with labels G subscript 1 over S checkpoint, G subscript 2 over M checkpoint and M over G subscript 1 checkpoint, plus the text Acceleration through checkpoints. Protein labels shown near the cycle: CDK4/6 Cyclin D, CDK2 Cyclin E, CDK1 Cyclin B, p16 and p21. Arrow continues downward to Post-senescence neoplastic emergent cell. Chemotherapy sequence, top to bottom: Chemotherapy icon → text HIF, NF-kB, SMAD, STAT3 → Cancer cell with nearby labels Fibroblast and CAFs. Arrow from CAFs points to a list: Lactate, Ketones, Glutamine, Fatty Acids, then arrow to Epithelial cell → Part ially-transformed epithelial cell → Self-renewal (circular arrow) → Cancer stem cell. Final convergence: a large arrow from the central Cancer cell area points downward to SPCs. Flowchart of radiotherapy and chemotherapy steps leading to SPCs, via DNA damage and cell transformation.

Concurrently, radiotherapy-induced lymphopenia and M2 macrophage polarization hinder the immune-mediated clearance of premalignant clones and may reactivate oncogenic viruses such as EBV in NHL. 60 , 62 Telomere shortening and reduced telomerase activity initiate breakage-fusion-bridge cycles, which promote chromosomal rearrangements and persistent genomic instability. 62 Most evidence derives from retrospective series with heterogeneous dosing and follow-up; therefore, prospective studies are required to delineate the dose-dependent risks of SPCs. 55

Chemotherapy: direct mutagenesis and microenvironment reprogramming

Alkylating agents and topoisomerase II inhibitors are potent mutagens that directly damage DNA. 63 , 64 Melphalan induces interstrand crosslinks, whereas etoposide causes double-strand breaks and KMT2A ( 11q23 ) translocations. 63 Cytotoxic agents also remodel the bone marrow niche by damaging mesenchymal stromal cells and inducing oxidative stress that activates HIF , NF-κB , and STAT3 pathways in stromal elements. 65 Metabolic reprogramming generates lactate, free fatty acids, and glutamine to fuel tumor growth. 66–69 Cancer-associated fibroblasts (CAFs) secrete proinflammatory cytokines (IL-6, IL-8), further promoting malignant transformation. 65 , 68 Both radiotherapy and chemotherapy impair T-cell and natural killer (NK)-cell function 70 , 71 ; platinum compounds reduce lymphocyte counts, undermining immunosurveillance and enabling viral reactivation. 6 , 54 , 63 Anti-angiogenic therapies (e.g., bevacizumab) may exacerbate hypoxia-driven tumorigenesis, and combination regimens can potentiate DNA damage-driven carcinogenesis. 72

CAR-T therapy–associated mechanisms

CAR-T therapy has significantly transformed the treatment landscape for refractory hematologic neoplasms; however, it carries a measurable risk of SPCs. 73–75 According to a 2024 report from the Center for International Blood and Marrow Transplant Research (CIBMTR), the cumulative incidence of SPCs was 4.30% (485 out of 11,345) in patients following CAR-T therapy, with a median follow-up of 13 months. 20 This absolute risk is not significantly higher than the baseline SPCs risk observed in heavily pretreated hematologic neoplasm populations and is comparable to the SPCs risk associated with HSCT or conventional salvage chemotherapy. 20 , 76 While CAR-T therapy may further exacerbate immune dysregulation in patients and promote the progression of pre-existing precancerous lesions to SPCs, there is currently no clinical evidence to suggest that CAR-T therapy directly induces the development of SPCs. 20 , 77 , 78

The mechanisms underlying these adverse events can be categorized into three key aspects ( Figure 4 ). (1) Insertional mutagenesis: The random integration of CAR transgenes via lentiviral vectors near oncogenes (e.g., MYC ) or within tumor suppressor genes (e.g., TP53 ) may lead to the malignant transformation of T-cells, resulting in the emergence of CAR-positive SPCs. This hypothesis is primarily supported by case reports and preclinical studies, with no large-scale clinical evidence confirming a causal relationship between CAR-T-associated insertional mutagenesis and SPCs. (2) Myeloid transformation: Pre-existing clonal hematopoiesis of indeterminate potential (CHIP), particularly in the presence of TP53 or TET2 mutations, confers resistance to lymphodepleting chemotherapy prior to CAR-T therapy (e.g., fludarabine/cyclophosphamide), thereby facilitating the selective expansion of CHIP clones and progression to myeloid SPCs (e.g., MDS, AML). (3) Immune dysregulation: Lymphodepleting chemotherapy, in conjunction with the antigen-restricted function of CAR-T cells, depletes CD8+ cytotoxic T lymphocytes, impairs antitumor surveillance, and allows solid tumor cells to evade immune control. 20 , 77–81 However, most studies examining CAR-T-associated SPCs have a follow-up duration of less than 2 y; thus, the long-term risk of SPCs (≥5 y) following CAR-T therapy remains unknown due to the relatively short clinical application history of this therapeutic approach. 20 , 77 , 82 Figure 4. Mechanisms of SPCs after CAR-T therapy. (A) Insertional mutagenesis: Lentiviral transduction results in random integration of car transgenes, which may induce malignant transformation of T cells. (B) Myeloid transformation: pre-existing clonal hematopoiesis of indeterminate potential (chip) (e.g., TP53 / TET2 -mutated clones) undergo expansion after lymphodepleting chemotherapy prior to CAR-T therapy, and subsequently progress to myeloid SPCs (e.g., MDS/AML). (C) Immune dysregulation promoting solid tumorigenesis: lymphodepletion and antigen-restricted CAR-T cell activity impair anti-tumor immune responses, allowing solid tumor cells to escape immune surveillance and ultimately leading to SPCs formation. The image contains three diagrams illustrating mechanisms of SPCs after CAR-T therapy. The image A showing insertional mutagenesis with lentiviral transduction leading to transgene-positive T-cell lymphoma. A target T cell undergoes lentiviral transduction, resulting in a novel sequence insertion, transforming into transgene-positive T-cell lymphoma. The image B showing myeloid transformation from hematopoietic stem cells to MDS/AML. A CHIP clone in bone marrow evolves through CAR-T infusion into myeloblasts, leading to clonal evolution and MDS/AML. The image C showing immune dysregulation favoring solid tumorigenesis. Tumor-specific CTLs and cancer cells undergo CAR-T infusion, leading to impaired antitumor immunity, inflammation, equilibrium and eventual escape of solid tumor cells. Three diagrams showing insertional mutagenesis, myeloid transformation and immune dysregulation in CAR-T therapy.

Tumor microenvironment remodeling

Inflammation and cytotoxic therapy synergistically reshape the hematopoietic ecosystem, facilitating the emergence of CHIP through cumulative genotoxic injury and replicative stress. Somatic mutations in DNMT3A , TET2 , and ASXL1 confer enhanced fitness to hematopoietic stem and progenitor cells (HSPCs) under conditions of oxidative damage and chronic inflammation. 83–85 However, the transition from benign CHIP to overt t-MNs or secondary solid cancers necessitates additional selective pressures arising directly from the therapeutic environment. 86 , 87 Under sustained genotoxic stress induced by chemotherapy and radiotherapy, the bone marrow niche experiences profound molecular and cellular reprogramming, shifting toward a pro-inflammatory and immunosuppressive phenotype characterized by elevated levels of IL-6, TNF-α, TGF-β1, and reactive ROS. 86 , 87 This remodeled microenvironment functions not merely as a passive byproduct of therapy, but as an active selective engine that preferentially expands pre-leukemic CHIP clones through several convergent mechanisms. (1) Dysregulation of the DNA Damage Response (DDR): Clones with mutations in TP53 and PPM1D exhibit impaired apoptosis following double-strand breaks induced by alkylating agents or ionizing radiation, thereby gaining a competitive advantage over wild-type hematopoietic stem and progenitor cells (HSPCs). Notably, PPM1D mutations are enriched under cytotoxic stress by suppressing p53 -dependent cell-cycle arrest and apoptosis, which facilitates post-treatment clonal expansion and dominance. 88–90 (2) Hijacking of Inflammatory Signaling: TET2 -mutated HSPCs show hyperactivation of the NLRP3 inflammasome and exaggerated secretion of IL-1β upon inflammatory stimulation, establishing a self-reinforcing circuit in which mutant clones both amplify and exploit the inflammatory environment. Concurrently, IL-6 and TNF-α released from therapy-activated stromal cells and macrophages engage JAK-STAT and NF-κB signaling pathways in DNMT3A -mutant clones, promoting their self-renewal and myeloid lineage bias while suppressing normal hematopoiesis. 91–93 (3) Metabolic Adaptation: Cytotoxic therapy induces persistent oxidative stress that favors clones with enhanced antioxidant defenses. Mutations in ASXL1 and IDH1/2 confer resistance to oxidative injury through mitochondrial reprogramming and epigenetic modulation, enabling the survival of damaged HSPCs that would otherwise be cleared. 84 , 94

This therapy-driven clonal selection is reinforced by niche components that sustain a pro-oncogenic microenvironment. Cancer-associated fibroblasts (CAFs), therapy-damaged mesenchymal stromal cells, and adipose-derived stromal elements secrete stem cell factor (SCF), insulin-like growth factor-1 (IGF-1), a range of pro-inflammatory cytokines, and extracellular matrix proteins. 95–97 Together, these elements establish a protective niche that promotes clonal persistence and confers resistance to further therapy. Importantly, the inflammatory network generated by CHIP clones extends beyond the marrow compartment; circulating IL-6, IL-1β, and other mediators infiltrate peripheral tissues, inducing immune checkpoint upregulation, angiogenesis, and stromal activation. 95–99 These systemic alterations foster a tumor-permissive environment that is conducive to the development of secondary solid malignancies. In summary, the tumor microenvironment transitions from a passive structural scaffold to an active architect of clonal evolution, wherein therapy-induced inflammation, oxidative stress, and DNA damage collaboratively redefine the selective landscape. This integrated cascade mechanistically links cytotoxic treatment exposure with the malignant transformation of pre-existing CHIP clones into therapy-related myeloid neoplasms and secondary primary cancers.

Circulating cell-free DNA

Emerging preclinical data suggest that cfDNA bearing oncogenic mutations can be internalized by recipient cells, disrupting DNA damage response pathways. 100–104 Although this mechanism remains speculative in clinical contexts, cfDNA represents a potential biomarker and therapeutic target for SPCs risk stratification. 100 , 101 Further investigation is warranted to confirm its oncogenic role in vivo and to explore its utility in personalized survivorship surveillance.

Clinical management and treatment strategies

With the increasing awareness of SPCs risk, it is essential to integrate prevention and risk-management strategies throughout the care continuum for survivors of hematologic malignancies. These strategies encompass risk-adapted modifications of initial treatment regimens, enhanced surveillance prior to SPCs diagnosis, and coordinated management by multidisciplinary teams (MDTs) following the onset of SPCs.

Treatment adjustment and risk mitigation

While CAR-T therapy has significantly advanced the treatment of relapsed or refractory hematologic malignancies, its association with SPCs underscores the need for vigilant risk mitigation strategies. 19 , 78 Recommended interventions include regular dermatologic examinations for the surveillance of non-melanoma skin cancers, 78 , 105 periodic hematologic assessments such as complete blood counts (CBCs), and comprehensive clinical evaluations, especially for patients with CH-related mutations like TP53 and TET2 . 106 , 107 Furthermore, age- and risk-adapted cancer screenings should be conducted in accordance with established guidelines for both the general population and cancer survivors. Additionally, monitoring of predictive biomarkers is essential to inform future risk-stratified surveillance protocols. 19 , 106

Surveillance and early detection

Given the elevated risk of SPCs in survivors of hematologic malignancies and the well-documented benefits of early detection, structured surveillance has become a cornerstone of survivorship care. 101 , 108 However, there is a notable absence of evidence-based, consensus-driven screening guidelines for SPCs tailored specifically to this population. Current practices rely on screening recommendations designed for the general population and survivors of solid tumors, with individual modifications based on prior treatment exposures (e.g., radiation fields, alkylating agents), genetic predisposition, and modifiable risk factors. 4 , 37

An optimal monitoring strategy should integrate: (1) standard-of-care screening tailored to therapy-related risks (e.g., breast magnetic resonance imaging [MRI] for female Hodgkin lymphoma survivors who received prior chest irradiation) 109 , 110 ; (2) heightened clinical vigilance for relevant signs and symptoms; and (3) the incorporation of emerging modalities, such as circulating tumor DNA (ctDNA) analysis, as supporting evidence becomes available. 100 , 101 The objective is to transition from uniform surveillance protocols to personalized, risk-adapted strategies that maximize early detection of SPCs while minimizing unnecessary procedures and patient burden. 4 , 111

Multidisciplinary team management

No standardized algorithm exists for SPCs arising from hematologic malignancies; therefore, optimal clinical decision-making requires an MDT approach. An effective MDT typically comprises hematologists, medical oncologists, radiation oncologists, surgical oncologists (as dictated by the subtype of SPCs), pathologists, radiologists, and supportive care specialists. 111 , 112 The MDT integrates critical information, including the status of the primary malignancy, the stage of SPCs, histology, molecular profile, cumulative treatment history, comorbidities, organ function, and performance status (assessed via comprehensive geriatric assessment in elderly patients). This information is crucial for prioritizing interventions, generally addressing the malignancy with the most immediate life-threatening risk, and for developing individualized treatment plans that maximize therapeutic benefits while minimizing cumulative toxicity. 111–114

Future directions: investigational strategies and technologies

Investigational approaches for risk mitigation

Preclinical and early-phase clinical research are investigating targeted interventions aimed at disrupting key pathways involved in therapy-related carcinogenesis. The strategies under examination focus on enhancing DNA repair mechanisms and eliminating pro-oncogenic cellular states that arise from cytotoxic treatments. For instance, preclinical models have shown that replenishing intracellular pools of nicotinamide adenine dinucleotide (NAD + ) through nicotinamide mononucleotide (NMN) facilitates poly (ADP-ribose) polymerase (PARP)-mediated DNA repair following fractionated radiotherapy. 115–117 Similarly, senolytic regimens, such as dasatinib in combination with quercetin, selectively eliminate senescent cells, thereby addressing a proposed precursor state for SPCs. 118 , 119 Although these approaches are mechanistically intriguing, they have not yet been validated in large-scale, randomized clinical trials to confirm their efficacy and safety for the prevention of SPCs.

Emerging monitoring technologies

Advances in minimally invasive monitoring hold promise for the earlier detection of SPCs and dynamic risk stratification. Liquid biopsy, particularly the analysis of ctDNA through next-generation sequencing (NGS), allows for the sensitive identification of tumor-specific genetic and epigenetic alterations, often providing a diagnostic advantage over conventional imaging modalities. 103 , 120 , 121 While ctDNA assays are well established in solid tumors, their utility in detecting molecular residual disease and early relapse in survivors of hematologic malignancies remains an active area of research. 121 , 122

Recent advances in multi-omics technologies-including genomics, epigenomics, transcriptomics, proteomics, and metabolomics-have enabled a comprehensive molecular dissection of therapy-related carcinogenesis and clonal evolution in survivors of hematologic malignancies. Integrated multi-omics studies now facilitate the identification of convergent pathways that link therapy-induced genotoxic stress to the emergence of secondary tumors. In the context of acute myeloid leukemia (AML), for instance, integrated proteogenomic analyses have shed light on the therapy-adaptive reprogramming of DNA repair and redox signaling networks, thereby providing a translational foundation for precision monitoring in survivors of SPCs. 123 Furthermore, pan-genomic frameworks have broadened our understanding of functional genome architecture and population-level genetic susceptibility to secondary malignancies. 124 These integrative models assist in delineating high-risk genotypes and informing target-specific surveillance pipelines. Beyond circulating ctDNA, emerging biomarker discoveries underscore molecular targets of pan-cancer significance. For example, ZNF165, a zinc finger transcriptional regulator aberrantly expressed in various malignancies, is recognized for its prognostic potential across different tumor types. 125 Similarly, tumor heterogeneity markers derived from single-cell multi-omics profiling enable the dynamic tracking of oncogenic clone evolution and therapeutic resistance. 126 Ultimately, these biomarkers may complement ctDNA assays to enhance precision risk stratification and the early detection of SPCs.

Novel therapeutic strategies

The management of established SPCs follows standard oncologic principles, including surgical resection, radiotherapy, chemotherapy, and molecularly targeted therapies. These approaches are tailored to the tumor’s histology, stage, and molecular profile, while also considering prior treatment exposures. 113 , 127 Emerging therapeutic modalities currently under clinical evaluation for the treatment of SPCs include antibody-drug conjugates (ADCs), which are engineered to selectively deliver cytotoxic payloads to tumor cells that express specific surface antigens. 128–130 Additionally, therapeutic cancer vaccines and adoptive immunotherapies are designed to generate antitumor immune responses against shared tumor-associated antigens or patient-specific neoantigens. Small-molecule inhibitors targeting oncogenic driver mutations, such as RAS and TP53 , are also being investigated. 131–133 Furthermore, modulators of the tumor microenvironment, which address stromal components like cancer-associated fibroblasts, present a novel strategy to disrupt protumoral niches and enhance treatment efficacy. 134 , 135 The optimal selection and sequencing of these therapeutic modalities within a MDT framework remain central to the individualized management of SPCs.

The role of the microbiome in modulating oncogenic signaling and systemic inflammation within the tumor microenvironment is increasingly recognized. Dysbiosis-driven alterations in immune tone and metabolic outputs can create pro-tumoral niches that are conducive to the development of SPCs. 136 Concurrently, therapeutic nanomaterials designed for microenvironmental regulation – such as immune-modulatory nanoparticles and redox-sensitive nanosystems – show promise in reprogramming stromal interactions and mitigating therapy-related carcinogenesis. 144 Collectively, these integrated approaches are reshaping the conceptual framework for monitoring SPCs, aligning mechanism-based insights with novel drug discovery paradigms.

Conclusion

SPCs present a significant long-term survivorship challenge for patients treated for hematologic malignancies. The pathogenesis of SPCs arises from a multifactorial interplay of various factors, with the cumulative treatment burden identified as the primary modifiable risk factor for their development. Current clinical management adheres to a risk-adapted framework led by a MDT, emphasizing the minimization of iatrogenic carcinogenic insults and the implementation of individualized early surveillance protocols. Despite these advancements, critical knowledge gaps remain: there are currently no disease-specific SPCs screening guidelines tailored for hematologic cancer survivors, and validated integrative risk prediction models that combine genetic profiles, prior therapeutic exposures, and clinical parameters are still lacking. Future research should prioritize the development of personalized risk-stratification tools, mechanistic studies that elucidate the ontogeny of therapy-induced SPCs, and the formulation of evidence-based MDT practice guidelines to translate proactive prevention into routine care. Furthermore, most emerging strategies for SPCs risk reduction and novel surveillance technologies are currently confined to preclinical or early-phase clinical evaluations. Robust validation in large prospective cohorts and dedicated translational investigations are essential before these approaches can be widely adopted in clinical practice. Addressing these gaps will be crucial for improving long-term outcomes and quality of life for survivors of hematologic malignancies.

This review is limited by the heterogeneity of primary data sources, variation in follow-up durations, and the scarcity of prospective clinical trials validating SPCs-specific surveillance. For clinicians, actionable steps include adopting individualized screening protocols aligned with therapeutic exposures and genetic predispositions, and integrating molecular surveillance tools – such as ctDNA and multi-omics panels – into survivorship programs. Researchers should prioritize large-scale longitudinal studies exploring therapy-induced genomic instability and develop standardized risk prediction models linking treatment history, omics signatures, and real-world outcomes. Robust multi-center collaborations will be vital to translate these insights into precision survivorship care. 137–143

Acknowledgments

We would like to thank the fruitfull discussions of all members of Dr. Qiong Wang’s research laboratory.

Qiong Wang , MD, PhD, is Chief Physician in the Clinical Laboratory of Wuxi People’s Hospital, China. Holding a Ph.D. in Laboratory Diagnostics from Nanjing Medical University, she has 16 y of clinical and research experience. Her work focuses on asthma pathogenesis and she leads quality-control initiatives that bridge lab data with bedside care.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

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